WorldWideScience

Sample records for real-time model attitude

  1. RTMOD: Real-Time MODel evaluation

    DEFF Research Database (Denmark)

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

    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-boundaryconsequences. 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 ofETEX, three dry runs (i.e. simulations in real-time of fictitious releases) were carried out...... 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 real-time communicationbetween dispersion modellers around the World and for fast and standardised information exchange on the most...

  2. Real-time modeling of heat distributions

    Energy Technology Data Exchange (ETDEWEB)

    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.

  3. RTMOD: Real-Time MODel evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Graziani, G; Galmarini, S. [Joint Research centre, Ispra (Italy); Mikkelsen, T. [Risoe National Lab., Wind Energy and Atmospheric Physics Dept. (Denmark)

    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

  4. Real time model for public transportation management

    Directory of Open Access Journals (Sweden)

    Ireneusz Celiński

    2014-03-01

    Full Text Available Background: The article outlines managing a public transportation fleet in the dynamic aspect. There are currently many technical possibilities of identifying demand in the transportation network. It is also possible to indicate legitimate basis of estimating and steering demand. The article describes a general public transportation fleet management concept based on balancing demand and supply. Material and methods: The presented method utilizes a matrix description of demand for transportation based on telemetric and telecommunication data. Emphasis was placed mainly on a general concept and not the manner in which data was collected by other researchers.  Results: The above model gave results in the form of a system for managing a fleet in real-time. The objective of the system is also to optimally utilize means of transportation at the disposal of service providers. Conclusions: The presented concept enables a new perspective on managing public transportation fleets. In case of implementation, the project would facilitate, among others, designing dynamic timetables, updated based on observed demand, and even designing dynamic points of access to public transportation lines. Further research should encompass so-called rerouting based on dynamic measurements of the characteristics of the transportation system.

  5. 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

  6. Method for Real-Time Model Based Structural Anomaly Detection

    Science.gov (United States)

    Smith, Timothy A. (Inventor); Urnes, James M., Sr. (Inventor); Reichenbach, Eric Y. (Inventor)

    2015-01-01

    A system and methods for real-time model based vehicle structural anomaly detection are disclosed. A real-time measurement corresponding to a location on a vehicle structure during an operation of the vehicle is received, and the real-time measurement is compared to expected operation data for the location to provide a modeling error signal. A statistical significance of the modeling error signal to provide an error significance is calculated, and a persistence of the error significance is determined. A structural anomaly is indicated, if the persistence exceeds a persistence threshold value.

  7. Unified Modeling of Complex Real-Time Control Systems

    OpenAIRE

    Hai, He; Yi-Fang, Zhong; Chi-lan, Cai

    2005-01-01

    Submitted on behalf of EDAA (http://www.edaa.com/); International audience; Complex real-time control system is a software dense and algorithms dense system, which needs modern software engineering techniques to design. UML is an object-oriented industrial standard modeling language, used more and more in real-time domain. This paper first analyses the advantages and problems of using UML for real-time control systems design. Then, it proposes an extension of UML-RT to support time-continuous...

  8. 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.

  9. 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.

  10. ARTEMIS: Ares Real Time Environments for Modeling, Integration, and Simulation

    Science.gov (United States)

    Hughes, Ryan; Walker, David

    2009-01-01

    This slide presentation reviews the use of ARTEMIS in the development and testing of the ARES launch vehicles. Ares Real Time Environment for Modeling, Simulation and Integration (ARTEMIS) is the real time simulation supporting Ares I hardware-in-the-loop (HWIL) testing. ARTEMIS accurately models all Ares/Orion/Ground subsystems which interact with Ares avionics components from pre-launch through orbit insertion The ARTEMIS System integration Lab, and the STIF architecture is reviewed. The functional components of ARTEMIS are outlined. An overview of the models and a block diagram is presented.

  11. 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.

  12. Model-Checking Real-Time Control Programs

    DEFF Research Database (Denmark)

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

    2000-01-01

    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...

  13. Real-time logic modelling on SpaceWire

    Science.gov (United States)

    Zhou, Qiang; Ma, Yunpeng; Fei, Haidong; Wang, Xingyou

    2017-04-01

    A SpaceWire is a standard for on-board satellite networks as the basis for future data-handling architectures. However, it cannot meet the deterministic requirement for safety/time critical application in spacecraft, where the delay of real-time (RT) message streams must be guaranteed. Therefore, SpaceWire-D is developed that provides deterministic delivery over a SpaceWire network. Formal analysis and verification of real-time systems is critical to their development and safe implementation, and is a prerequisite for obtaining their safety certification. Failure to meet specified timing constraints such as deadlines in hard real-time systems may lead to catastrophic results. In this paper, a formal verification method, Real-Time Logic (RTL), has been proposed to specify and verify timing properties of SpaceWire-D network. Based on the principal of SpaceWire-D protocol, we firstly analyze the timing properties of fundamental transactions, such as RMAP WRITE, and RMAP READ. After that, the RMAP WRITE transaction structure is modeled in Real-Time Logic (RTL) and Presburger Arithmetic representations. And then, the associated constraint graph and safety analysis is provided. Finally, it is suggested that RTL method can be useful for the protocol evaluation and provision of recommendation for further protocol evolutions.

  14. Real-time multi-model decadal climate predictions

    NARCIS (Netherlands)

    Smith, D.M.; Scaife, A.A.; Boer, G.J.; Caian, M.; Doblas-Reyes, F.J.; Guemas, V.; Hawkins, E.; Hazeleger, W.; Hermanson, L.; Ho, C.K.; Ishii, M.; Kharin, V.; Kimoto, M.; Kirtman, B.; Lean, J.; Matei, D.; Merryfield, W.J.; Muller, W.A.; Pohlmann, H.; Rosati, A.; Wouters, B.; Wyser, K.

    2013-01-01

    We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus

  15. 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

  16. 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.

  17. Programming Models for Concurrency and Real-Time

    Science.gov (United States)

    Vitek, Jan

    Modern real-time applications are increasingly large, complex and concurrent systems which must meet stringent performance and predictability requirements. Programming those systems require fundamental advances in programming languages and runtime systems. This talk presents our work on Flexotasks, a programming model for concurrent, real-time systems inspired by stream-processing and concurrent active objects. Some of the key innovations in Flexotasks are that it support both real-time garbage collection and region-based memory with an ownership type system for static safety. Communication between tasks is performed by channels with a linear type discipline to avoid copying messages, and by a non-blocking transactional memory facility. We have evaluated our model empirically within two distinct implementations, one based on Purdue’s Ovm research virtual machine framework and the other on Websphere, IBM’s production real-time virtual machine. We have written a number of small programs, as well as a 30 KLOC avionics collision detector application. We show that Flexotasks are capable of executing periodic threads at 10 KHz with a standard deviation of 1.2us and have performance competitive with hand coded C programs.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. Simplified Model of Brushless Synchronous Generator for Real Time Simulation

    CERN Document Server

    Lopez, M D; Rebollo, E; Blanquez, F R

    2015-01-01

    This paper presents a simplified model of brushless synchronous machine for saving hardware resources in a real time simulation system. Firstly, a brushless excitation system model is described. Thereafter, the simplified transfer function of an AC exciter and rotating diodes of the brushless excitation system is estimated. Finally, the complete system is simulated, comparing the main generator's voltage with both detailed and simplified excitation systems in several scenarios. These results show the accuracy of the simplified model against the detailed simulation model, resulting on an important hardware resources savings.

  3. 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

  4. Further development of the attitude difference method for estimating deflections of the vertical in real time

    Science.gov (United States)

    Zhu, Jing; Zhou, Zebo; Li, Yong; Rizos, Chris; Wang, Xingshu

    2016-07-01

    An improvement of the attitude difference method (ADM) to estimate deflections of the vertical (DOV) in real time is described in this paper. The ADM without offline processing estimates the DOV with a limited accuracy due to the response delay. The proposed model selection-based self-adaptive delay feedback (SDF) method takes the results of the ADM as the a priori information, then uses fitting and extrapolation to estimate the DOV at the current epoch. The active region selection factor F th is used to take full advantage of the Earth model EGM2008 and the SDF with different DOV exhibitions. The factors which affect the DOV estimation accuracy are analyzed and modeled. An external observation which is specified by the velocity difference between the global navigation satellite system (GNSS) and the inertial navigation system (INS) with DOV compensated is used to select the optimal model. The response delay induced by the weak observability of an integrated INS/GNSS to the violent DOV disturbances in the ADM is compensated. The DOV estimation accuracy of the SDF method is improved by approximately 40% and 50% respectively compared to that of the EGM2008 and the ADM. With an increase in GNSS accuracy, the DOV estimation accuracy could improve further.

  5. Integration of a Motion Capture System into a Spacecraft Simulator for Real-Time Attitude Control

    Science.gov (United States)

    2016-08-16

    DISTRIBUTION A. Approved for public release: distribution unlimited. Integration of a Motion Capture System into a Spacecraft Simulator for Real-Time...integrated with a Phase- Space Impulse X2 motion capture system. This system calculates the testbed’s inertial attitude, which can be used to simulate various...generate measurements via another source. To that end, a PhaseSpace Impulse X2 motion capture system has been integrated with the ACSPG and a wireless

  6. A Model for Industrial Real-Time Systems

    DEFF Research Database (Denmark)

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

    2015-01-01

    industrial systems: (i) compositional modeling with reusable designs for different contexts, and (ii) an automated state-space reduction technique. Timed process automata model dynamic networks of continuous-time communicating control processes which can activate other processes. We show how to automatically......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...... establish safety and reachability properties of TPA by reduction to solving timed games. To mitigate the state-space explosion problem, an automated state-space reduction technique using compositional reasoning and aggressive abstractions is also proposed....

  7. A Formal Model for Real-Time Parallel Computation

    Energy Technology Data Exchange (ETDEWEB)

    Hui, Peter SY; Chikkagoudar, Satish

    2012-12-29

    The imposition of real-time constraints on a parallel computing environment--- specifically high-performance, cluster-computing systems--- introduces a variety of challenges with respect to the formal verification of the system's timing properties. In this paper, we briefly motivate the need for such a system, and we introduce an automaton-based method for performing such formal verification. We define the concept of a consistent parallel timing system: a hybrid system consisting of a set of timed automata (specifically, timed Buechi automata as well as a timed variant of standard finite automata), intended to model the timing properties of a well-behaved real-time parallel system. Finally, we give a brief case study to demonstrate the concepts in the paper: a parallel matrix multiplication kernel which operates within provable upper time bounds. We give the algorithm used, a corresponding consistent parallel timing system, and empirical results showing that the system operates under the specified timing constraints.

  8. A Formal Model For Real-Time Parallel Computation

    Directory of Open Access Journals (Sweden)

    Peter Hui

    2012-12-01

    Full Text Available The imposition of real-time constraints on a parallel computing environment– specifically high-performance, cluster-computing systems– introduces a variety of challenges with respect to the formal verification of the system's timing properties. In this paper, we briefly motivate the need for such a system, and we introduce an automaton-based method for performing such formal verification. We define the concept of a consistent parallel timing system: a hybrid system consisting of a set of timed automata (specifically, timed Buchi automata as well as a timed variant of standard finite automata, intended to model the timing properties of a well-behaved real-time parallel system. Finally, we give a brief case study to demonstrate the concepts in the paper: a parallel matrix multiplication kernel which operates within provable upper time bounds. We give the algorithm used, a corresponding consistent parallel timing system, and empirical results showing that the system operates under the specified timing constraints.

  9. 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.

  10. Model-Based Real-Time Head Tracking

    Directory of Open Access Journals (Sweden)

    Ström Jacob

    2002-01-01

    Full Text Available This paper treats real-time tracking of a human head using an analysis by synthesis approach. The work is based on the Structure from Motion (SfM algorithm from Azarbayejani and Pentland (1995. We will analyze the convergence properties of the SfM algorithm for planar objects, and extend it to handle new points. The extended algorithm is then used for head tracking. The system tracks feature points in the image using a texture mapped three-dimensional model of the head. The texture is updated adaptively so that points in the ear region can be tracked when the user′s head is rotated far, allowing out-of-plane rotation of up to without losing track. The covariance of the - and the -coordinates are estimated and forwarded to the Kalman filter, making the tracker robust to occlusion. The system automatically detects tracking failure and reinitializes the algorithm using information gathered in the original initialization process.

  11. Designers Workbench: Towards Real-Time Immersive Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Kuester, F; Duchaineau, M A; Hamann, B; Joy, K I; Ma, K L

    2001-10-03

    This paper introduces the DesignersWorkbench, 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 (CAM), and computer-aided engineering (CAE) systems has established a new backbone of modern industrial product development. However, traditionally a product design frequently originates from a clay model that, after digitization, forms the basis for the numerical description of CAD primitives. The DesignersWorkbench aims at closing this technology or ''digital gap'' experienced by design and CAD engineers by transforming the classical design paradigm into its filly integrated digital and virtual analog allowing collaborative development in a semi-immersive virtual environment. This project emphasizes two key components from the classical product design cycle: freeform modeling and analysis. In the freeform 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.

  12. Design, real-time modelling, simulation and digital implementation ...

    Indian Academy of Sciences (India)

    locked loop-based auto-synchronising current-sourced converter for an induction heating prototype. MOLAY ROY MAINAK SENGUPTA ... Keywords. Induction heating; current source inverter (CSI); phase-locked loop; FPGA; real-time simulation.

  13. Eye tracker uncertainty analysis and modelling in real time

    Science.gov (United States)

    Fornaser, A.; De Cecco, M.; Leuci, M.; Conci, N.; Daldoss, M.; Armanini, A.; Maule, L.; De Natale, F.; Da Lio, M.

    2017-01-01

    Techniques for tracking the eyes took place since several decades for different applications that range from military, to education, entertainment and clinics. The existing systems are in general of two categories: precise but intrusive or comfortable but less accurate. The idea of this work is to calibrate an eye tracker of the second category. In particular we have estimated the uncertainty both in nominal and in case of variable operating conditions. We took into consideration different influencing factors such as: head movement and rotation, eyes detected, target position on the screen, illumination and objects in front of the eyes. Results proved that the 2D uncertainty can be modelled as a circular confidence interval as far as there is no stable principal directions in both the systematic and the repeatability effects. This confidence region was also modelled as a function of the current working conditions. In this way we can obtain a value of the uncertainty that is a function of the operating condition estimated in real time opening the field to new applications that reconfigure the human machine interface as a function of the operating conditions. Examples can range from option buttons reshape, local zoom dynamically adjusted, speed optimization to regulate interface responsiveness, the possibility to take into account the uncertainty associated to a particular interaction. Furthermore, in the analysis of visual scanning patterns, the resulting Point of Regard maps would be associated with proper confidence levels thus allowing to draw accurate conclusions. We conducted an experimental campaign to estimate and validate the overall modelling procedure obtaining valid results in 86% of the cases.

  14. Real-Time GNSS-Based Attitude Determination in the Measurement Domain.

    Science.gov (United States)

    Zhao, Lin; Li, Na; Li, Liang; Zhang, Yi; Cheng, Chun

    2017-02-05

    A multi-antenna-based GNSS receiver is capable of providing high-precision and drift-free attitude solution. Carrier phase measurements need be utilized to achieve high-precision attitude. The traditional attitude determination methods in the measurement domain and the position domain resolve the attitude and the ambiguity sequentially. The redundant measurements from multiple baselines have not been fully utilized to enhance the reliability of attitude determination. A multi-baseline-based attitude determination method in the measurement domain is proposed to estimate the attitude parameters and the ambiguity simultaneously. Meanwhile, the redundancy of attitude resolution has also been increased so that the reliability of ambiguity resolution and attitude determination can be enhanced. Moreover, in order to further improve the reliability of attitude determination, we propose a partial ambiguity resolution method based on the proposed attitude determination model. The static and kinematic experiments were conducted to verify the performance of the proposed method. When compared with the traditional attitude determination methods, the static experimental results show that the proposed method can improve the accuracy by at least 0.03° and enhance the continuity by 18%, at most. The kinematic result has shown that the proposed method can obtain an optimal balance between accuracy and reliability performance.

  15. 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

  16. 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

  17. A Provenance Model for Real-Time Water Information Systems

    Science.gov (United States)

    Liu, Q.; Bai, Q.; Zednik, S.; Taylor, P.; Fox, P. A.; Taylor, K.; Kloppers, C.; Peters, C.; Terhorst, A.; West, P.; Compton, M.; Shu, Y.; Provenance Management Team

    2010-12-01

    Generating hydrological data products, such as flow forecasts, involves complex interactions among instruments, data simulation models, computational facilities and data providers. Correct interpretation of the data produced at various stages requires good understanding of how data was generated or processed. Provenance describes the lineage of a data product. Making provenance information accessible to hydrologists and decision makers not only helps to determine the data’s value, accuracy and authorship, but also enables users to determine the trustworthiness of the data product. In the water domain, WaterML2 [1] is an emerging standard which describes an information model and format for the publication of water observations data in XML. The W3C semantic sensor network incubator group (SSN-XG) [3] is producing ontologies for the description of sensor configurations. By integrating domain knowledge of this kind into the provenance information model, the integrated information model will enable water domain researchers and water resource managers to better analyse how observations and derived data products were generated. We first introduce the Proof Mark Language (PML2) [2], WaterML2 and the SSN-XG sensor ontology as the proposed provenance representation formalism. Then we describe some initial implementations how these standards could be integrated to represent the lineage of water information products. Finally we will highlight how the provenance model for a distributed real-time water information system assists the interpretation of the data product and establishing trust. Reference [1] Taylor, P., Walker, G., Valentine, D., Cox, Simon: WaterML2.0: Harmonising standards for water observation data. Geophysical Research Abstracts. Vol. 12. [2] da Silva, P.P., McGuinness, D.L., Fikes, R.: A proof markup language for semantic web services. Inf. Syst. 31(4) (2006), 381-395. [3] W3C Semantic Sensor Network Incubator Group http://www.w3.org/2005/Incubator

  18. Real-time multi-model decadal climate predictions

    Science.gov (United States)

    Smith, Doug M.; Scaife, Adam A.; Boer, George J.; Caian, Mihaela; Doblas-Reyes, Francisco J.; Guemas, Virginie; Hawkins, Ed; Hazeleger, Wilco; Hermanson, Leon; Ho, Chun Kit; Ishii, Masayoshi; Kharin, Viatcheslav; Kimoto, Masahide; Kirtman, Ben; Lean, Judith; Matei, Daniela; Merryfield, William J.; Müller, Wolfgang A.; Pohlmann, Holger; Rosati, Anthony; Wouters, Bert; Wyser, Klaus

    2013-12-01

    We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus view to prevent over-confidence in forecasts from any single model, and establish current collective capability. We stress that the forecast is experimental, since the skill of the multi-model system is as yet unknown. Nevertheless, the forecast systems used here are based on models that have undergone rigorous evaluation and individually have been evaluated for forecast skill. Moreover, it is important to publish forecasts to enable open evaluation, and to provide a focus on climate change in the coming decade. Initialized forecasts of the year 2011 agree well with observations, with a pattern correlation of 0.62 compared to 0.31 for uninitialized projections. In particular, the forecast correctly predicted La Niña in the Pacific, and warm conditions in the north Atlantic and USA. A similar pattern is predicted for 2012 but with a weaker La Niña. Indices of Atlantic multi-decadal variability and Pacific decadal variability show no signal beyond climatology after 2015, while temperature in the Niño3 region is predicted to warm slightly by about 0.5 °C over the coming decade. However, uncertainties are large for individual years and initialization has little impact beyond the first 4 years in most regions. Relative to uninitialized forecasts, initialized forecasts are significantly warmer in the north Atlantic sub-polar gyre and cooler in the north Pacific throughout the decade. They are also significantly cooler in the global average and over most land and ocean regions out to several years ahead. However, in the absence of volcanic eruptions, global temperature is predicted to continue to rise, with each year from 2013 onwards having a 50 % chance of exceeding the

  19. 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.

  20. Extending the Real-Time Maude Semantics of Ptolemy to Hierarchical DE Models

    Directory of Open Access Journals (Sweden)

    Peter Csaba Ölveczky

    2010-09-01

    Full Text Available This paper extends our Real-Time Maude formalization of the semantics of flat Ptolemy II discrete-event (DE models to hierarchical models, including modal models. This is a challenging task that requires combining synchronous fixed-point computations with hierarchical structure. The synthesis of a Real-Time Maude verification model from a Ptolemy II DE model, and the formal verification of the synthesized model in Real-Time Maude, have been integrated into Ptolemy II, enabling a model-engineering process that combines the convenience of Ptolemy II DE modeling and simulation with formal verification in Real-Time Maude.

  1. Real-time single-frequency GPS/MEMS-IMU attitude determination of lightweight UAVs.

    Science.gov (United States)

    Eling, Christian; Klingbeil, Lasse; Kuhlmann, Heiner

    2015-10-16

    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.

  2. Verifying Ptolemy II Discrete-Event Models Using Real-Time Maude

    Science.gov (United States)

    Bae, Kyungmin; Ölveczky, Peter Csaba; Feng, Thomas Huining; Tripakis, Stavros

    This paper shows how Ptolemy II discrete-event (DE) models can be formally analyzed using Real-Time Maude. We formalize in Real-Time Maude the semantics of a subset of hierarchical Ptolemy II DE models, and explain how the code generation infrastructure of Ptolemy II has been used to automatically synthesize a Real-Time Maude verification model from a Ptolemy II design model. This enables a model-engineering process that combines the convenience of Ptolemy II DE modeling and simulation with formal verification in Real-Time Maude.

  3. 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.

  4. 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....

  5. 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.

  6. 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.

  7. 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.

  8. Real-time model based electrical powered wheelchair control.

    Science.gov (United States)

    Wang, Hongwu; Salatin, Benjamin; Grindle, Garrett G; Ding, Dan; Cooper, Rory A

    2009-12-01

    The purpose of this study was to evaluate the effects of three different control methods on driving speed variation and wheel slip of an electric-powered wheelchair (EPW). A kinematic model as well as 3D dynamic model was developed to control the velocity and traction of the wheelchair. A smart wheelchair platform was designed and built with a computerized controller and encoders to record wheel speeds and to detect the slip. A model based, a proportional-integral-derivative (PID) and an open-loop controller were applied with the EPW driving on four different surfaces at three specified speeds. The speed errors, variation, rise time, settling time and slip coefficient were calculated and compared for a speed step-response input. Experimental results showed that model based control performed best on all surfaces across the speeds.

  9. Real-Time Global Nonlinear Aerodynamic Modeling for Learn-To-Fly

    Science.gov (United States)

    Morelli, Eugene A.

    2016-01-01

    Flight testing and modeling techniques were developed to accurately identify global nonlinear aerodynamic models for aircraft in real time. The techniques were developed and demonstrated during flight testing of a remotely-piloted subscale propeller-driven fixed-wing aircraft using flight test maneuvers designed to simulate a Learn-To-Fly scenario. Prediction testing was used to evaluate the quality of the global models identified in real time. The real-time global nonlinear aerodynamic modeling algorithm will be integrated and further tested with learning adaptive control and guidance for NASA Learn-To-Fly concept flight demonstrations.

  10. 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...

  11. Power quality analyzer device modeling by real time SIMULINK MATLAB

    Energy Technology Data Exchange (ETDEWEB)

    Martins, C.H.N.; Silva, L.R.M.; Fabri, D.F.; Duque, C.A. [Federal University of Juiz de Fora (UFJF), MG (Brazil)], Emails: chnmartins@yahoo.com.br, leandro.manso@engenharia.ufjf.br, Diego.fabri@engenharia.ufjf.br, Carlos.duque@ufjf.br; Ribeiro, P.F. [Calvin College, Grand Rapids, MI (United States)], E-mail: pfribeiro@ieee.org

    2009-07-01

    The expansion of electronic devices have increased non linear loads. The effect is high levels of electric disturbances and EMC and EMI interferences. The control of power quality parameters are of primordial importance to ensure minimal power quality. This paper deals with the modeling, simulation and development of a device capable of measuring electrical events. (author)

  12. 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.

  13. Real Time Updating in Distributed Urban Rainfall Runoff Modelling

    DEFF Research Database (Denmark)

    Borup, Morten; Madsen, Henrik

    to the hydrodynamic model and is not capable of updating the water levels in pipes and basins explicitly. The statistical data assimilation method the Ensemble Kalman Filter (EnKF) was investigated as a tool to update all the state variables in a DUDM. The method was tested in synthetic experiments as well...... systems (and elsewhere) do not measure the quantity they are observing continuously. A new method was developed for utilising this kind of range-limited observations better when using the EnKF. The method works by counteracting the ensemble in spreading into to observable range when the lack...

  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 steady state hydraulic model that will be used within a real-time dynamic hydraulic model (DHM). The Council for Scientific and Industrial Research (CSIR) water distribution network (WDN) is used as a pilot study for this purpose. A hydraulic analysis...

  15. Safety analytics for integrating crash frequency and real-time risk modeling for expressways.

    Science.gov (United States)

    Wang, Ling; Abdel-Aty, Mohamed; Lee, Jaeyoung

    2017-07-01

    To find crash contributing factors, there have been numerous crash frequency and real-time safety studies, but such studies have been conducted independently. Until this point, no researcher has simultaneously analyzed crash frequency and real-time crash risk to test whether integrating them could better explain crash occurrence. Therefore, this study aims at integrating crash frequency and real-time safety analyses using expressway data. A Bayesian integrated model and a non-integrated model were built: the integrated model linked the crash frequency and the real-time models by adding the logarithm of the estimated expected crash frequency in the real-time model; the non-integrated model independently estimated the crash frequency and the real-time crash risk. The results showed that the integrated model outperformed the non-integrated model, as it provided much better model results for both the crash frequency and the real-time models. This result indicated that the added component, the logarithm of the expected crash frequency, successfully linked and provided useful information to the two models. This study uncovered few variables that are not typically included in the crash frequency analysis. For example, the average daily standard deviation of speed, which was aggregated based on speed at 1-min intervals, had a positive effect on crash frequency. In conclusion, this study suggested a methodology to improve the crash frequency and real-time models by integrating them, and it might inspire future researchers to understand crash mechanisms better. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. 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.

  17. Model-Checking of Component-Based Event-Driven Real-Time Embedded Software

    National Research Council Canada - National Science Library

    Gu, Zonghua; Shin, Kang G

    2005-01-01

    .... We discuss application of model-checking to verify system-level concurrency properties of component-based real-time embedded software based on CORBA Event Service, using Avionics Mission Computing...

  18. Real-time Estimation of UAS Performance Using Efficient Sampling of Functional Models Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Numerica proposes to developed advanced algorithms for constructing a UAS vehicle model from ATC surveillance data in real-time. Using functional descriptions of...

  19. Model-Based Real Time Assessment of Capability Left for Spacecraft Under Failure Mode Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed project is aimed at developing a model based diagnostics system for spacecraft that will allow real time assessment of its state, while it is impacted...

  20. Formal Model Engineering for Embedded Systems Using Real-Time Maude

    Directory of Open Access Journals (Sweden)

    Peter Csaba Ölveczky

    2011-06-01

    Full Text Available This paper motivates why Real-Time Maude should be well suited to provide a formal semantics and formal analysis capabilities to modeling languages for embedded systems. One can then use the code generation facilities of the tools for the modeling languages to automatically synthesize Real-Time Maude verification models from design models, enabling a formal model engineering process that combines the convenience of modeling using an informal but intuitive modeling language with formal verification. We give a brief overview six fairly different modeling formalisms for which Real-Time Maude has provided the formal semantics and (possibly formal analysis. These models include behavioral subsets of the avionics modeling standard AADL, Ptolemy II discrete-event models, two EMF-based timed model transformation systems, and a modeling language for handset software.

  1. GPU-Accelerated Real-Time Path Planning and the Predictable Execution Model

    OpenAIRE

    Forsberg, Björn; Palossi, Daniele; Marongiu, Andrea; Benini, Luca

    2017-01-01

    Path planning is one of the key functional blocks for autonomous vehicles constantly updating their route in real-time. Heterogeneous many-cores are appealing candidates for its execution, but the high degree of resource sharing results in very unpredictable timing behavior. The predictable execution model (PREM) has the potential to enable the deployment of real-time applications on top of commercial off-the-shelf (COTS) heterogeneous systems by separating compute and memory operations, and ...

  2. Real-Time Gait Event Detection Based on Kinematic Data Coupled to a Biomechanical Model ?

    OpenAIRE

    Lambrecht, Stefan; Harutyunyan, Anna; Tanghe, Kevin; Afschrift, Maarten; De Schutter, Joris; Jonkers, Ilse

    2017-01-01

    Real-time detection of multiple stance events, more specifically initial contact (IC), foot flat (FF), heel off (HO), and toe off (TO), could greatly benefit neurorobotic (NR) and neuroprosthetic (NP) control. Three real-time threshold-based algorithms have been developed, detecting the aforementioned events based on kinematic data in combination with a biomechanical model. Data from seven subjects walking at three speeds on an instrumented treadmill were used to validate the presented algori...

  3. Real-time capable first principle based modelling of tokamak turbulent transport

    CERN Document Server

    Breton, S; Felici, F; Imbeaux, F; Aniel, T; Artaud, J F; Baiocchi, B; Bourdelle, C; Camenen, Y; Garcia, J

    2015-01-01

    A real-time capable core turbulence tokamak transport model is developed. This model is constructed from the regularized nonlinear regression of quasilinear gyrokinetic transport code output. The regression is performed with a multilayer perceptron neural network. The transport code input for the neural network training set consists of five dimensions, and is limited to adiabatic electrons. The neural network model successfully reproduces transport fluxes predicted by the original quasilinear model, while gaining five orders of magnitude in computation time. The model is implemented in a real-time capable tokamak simulator, and simulates a 300s ITER discharge in 10s. This proof-of-principle for regression based transport models anticipates a significant widening of input space dimensionality and physics realism for future training sets. This aims to provide unprecedented computational speed coupled with first-principle based physics for real-time control and integrated modelling applications.

  4. PM1 2-hour refined Near Real Time (NRT) Spacecraft Attitude data (MODIS Ancillary Data)

    Data.gov (United States)

    National Aeronautics and Space Administration — PM1ATTNR is the Aqua 2-hour spacecraft refined attitude data file in native format. The file name format is the following: PM1ATTNR.Pyyyyddd.hhmm.vvv.yyyydddhhmmss...

  5. Model based analysis of real-time PCR data from DNA binding dye protocols

    Directory of Open Access Journals (Sweden)

    Salibe Mariano C

    2007-03-01

    Full Text Available Abstract Background Reverse transcription followed by real-time PCR is widely used for quantification of specific mRNA, and with the use of double-stranded DNA binding dyes it is becoming a standard for microarray data validation. Despite the kinetic information generated by real-time PCR, most popular analysis methods assume constant amplification efficiency among samples, introducing strong biases when amplification efficiencies are not the same. Results We present here a new mathematical model based on the classic exponential description of the PCR, but modeling amplification efficiency as a sigmoidal function of the product yield. The model was validated with experimental results and used for the development of a new method for real-time PCR data analysis. This model based method for real-time PCR data analysis showed the best accuracy and precision compared with previous methods when used for quantification of in-silico generated and experimental real-time PCR results. Moreover, the method is suitable for the analyses of samples with similar or dissimilar amplification efficiency. Conclusion The presented method showed the best accuracy and precision. Moreover, it does not depend on calibration curves, making it ideal for fully automated high-throughput applications.

  6. 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...

  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. Near Real-Time Closed-Loop Optimal Control Feedback for Spacecraft Attitude Maneuvers

    Science.gov (United States)

    2009-03-01

    slightly shorter path due to the Sagnac effect. A sensor also located at either end of the fiber optic coil is characterized to measure the effects...A. Bosse, and S. Fisher. A Integrated GPS / Gyro / Smart Structures Architecture for Attitude Determination and Baseline Metrology . In Proceedings of

  9. 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...

  10. 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.

  11. 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

    has been implemented in a tool, named SARTS, successfully used to verify the schedulability of a real-time sorting machine consisting of two periodic and two sporadic tasks. SARTS has also been applied on a number of smaller examples to investigate properties of our approach.......In this paper, we present a novel approach to schedulability analysis of Safety Critical Hard Real-Time Java programs. The approach is based on a translation of programs, written in the Safety Critical Java profile introduced in [21] for the Java Optimized Processor [18], to timed automata models...

  12. Biomimetic-Based Output Feedback for Attitude Stabilization of Rigid Bodies: Real-Time Experimentation on a Quadrotor

    Directory of Open Access Journals (Sweden)

    José Fermi Guerrero-Castellanos

    2015-08-01

    Full Text Available The present paper deals with the development of bounded feedback control laws mimicking the strategy adopted by flapping flyers to stabilize the attitude of systems falling within the framework of rigid bodies. Flapping flyers are able to orient their trajectory without any knowledge of their current attitude and without any attitude computation. They rely on the measurements of some sensitive organs: halteres, leg sensilla and magnetic sense, which give information about their angular velocity and the orientation of gravity and magnetic field vectors. Therefore, the proposed feedback laws are computed using direct inertial sensors measurements, that is vector observations with/without angular velocity measurements. Hence, the attitude is not explicitly required. This biomimetic approach is very simple, requires little computational power and is suitable for embedded applications on small control units. The boundedness of the control signal is taken into consideration through the design of the control laws by saturation of the actuators’ input. The asymptotic stability of the closed loop system is proven by Lyapunov analysis. Real-time experiments are carried out on a quadrotor using MEMS inertial sensors in order to emphasize the efficiency of this biomimetic strategy by showing the convergence of the body’s states in hovering mode, as well as the robustness with respect to external disturbances.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. Multitask Deep Learning models for real-time deployment in embedded systems

    OpenAIRE

    Martí i Rabadán, Miquel

    2017-01-01

    Multitask Learning (MTL) was conceived as an approach to improve thegeneralization ability of machine learning models. When applied to neu-ral networks, multitask models take advantage of sharing resources forreducing the total inference time, memory footprint and model size. Wepropose MTL as a way to speed up deep learning models for applicationsin which multiple tasks need to be solved simultaneously, which is par-ticularly useful in embedded, real-time systems such as the ones foundin auto...

  18. 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.

  19. 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.

  20. Real-time PCR machine system modeling and a systematic approach for the robust design of a real-time PCR-on-a-chip system.

    Science.gov (United States)

    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 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.

  1. Model-based reconstruction for real-time phase-contrast flow MRI: Improved spatiotemporal accuracy.

    Science.gov (United States)

    Tan, Zhengguo; Roeloffs, Volkert; Voit, Dirk; Joseph, Arun A; Untenberger, Markus; Merboldt, K Dietmar; Frahm, Jens

    2017-03-01

    To develop a model-based reconstruction technique for real-time phase-contrast flow MRI with improved spatiotemporal accuracy in comparison to methods using phase differences of two separately reconstructed images with differential flow encodings. The proposed method jointly computes a common image, a phase-contrast map, and a set of coil sensitivities from every pair of flow-compensated and flow-encoded datasets obtained by highly undersampled radial FLASH. Real-time acquisitions with five and seven radial spokes per image resulted in 25.6 and 35.7 ms measuring time per phase-contrast map, respectively. The signal model for phase-contrast flow MRI requires the solution of a nonlinear inverse problem, which is accomplished by an iteratively regularized Gauss-Newton method. Aspects of regularization and scaling are discussed. The model-based reconstruction was validated for a numerical and experimental flow phantom and applied to real-time phase-contrast MRI of the human aorta for 10 healthy subjects and 2 patients. Under all conditions, and compared with a previously developed real-time flow MRI method, the proposed method yields quantitatively accurate phase-contrast maps (i.e., flow velocities) with improved spatial acuity, reduced phase noise and reduced streaking artifacts. This novel model-based reconstruction technique may become a new tool for clinical flow MRI in real time. Magn Reson Med 77:1082-1093, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

  2. Modelling water quality in drinking water distribution networks from real-time direction data

    OpenAIRE

    Nazarovs, S.; Dejus, S.; Juhna, T.

    2012-01-01

    Modelling of contamination spread and location of a contamination source in a water distribution network is an important task. There are several simulation tools developed, however the significant part of them is based on hydraulic models that need node demands as input data that sometimes may result in false negative results and put users at risk. The paper considers applicability of a real-time flow direction data based model for contaminant transport in a distribution network of a city and...

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

    OpenAIRE

    Lu, Hua-pu; Sun, Zhi-yuan; Qu, Wen-cong; Wang, Ling

    2015-01-01

    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 ...

  4. A multitask deep learning model for real-time deployment in embedded systems

    OpenAIRE

    Martí, Miquel; Maki, Atsuto

    2017-01-01

    We propose an approach to Multitask Learning (MTL) to make deep learning models faster and lighter for applications in which multiple tasks need to be solved simultaneously, which is particularly useful in embedded, real-time systems. We develop a multitask model for both Object Detection and Semantic Segmentation and analyze the challenges that appear during its training. Our multitask network is 1.6x faster, lighter and uses less memory than deploying the single-task models in parallel. We ...

  5. 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.

  6. A Robust Nonlinear Observer for Real-Time Attitude Estimation Using Low-Cost MEMS Inertial Sensors

    Science.gov (United States)

    Guerrero-Castellanos, José Fermi; Madrigal-Sastre, Heberto; Durand, Sylvain; Torres, Lizeth; Muñoz-Hernández, German Ardul

    2013-01-01

    This paper deals with the attitude estimation of a rigid body equipped with angular velocity sensors and reference vector sensors. A quaternion-based nonlinear observer is proposed in order to fuse all information sources and to obtain an accurate estimation of the attitude. It is shown that the observer error dynamics can be separated into two passive subsystems connected in “feedback”. Then, this property is used to show that the error dynamics is input-to-state stable when the measurement disturbance is seen as an input and the error as the state. These results allow one to affirm that the observer is “robustly stable”. The proposed observer is evaluated in real-time with the design and implementation of an Attitude and Heading Reference System (AHRS) based on low-cost MEMS (Micro-Electro-Mechanical Systems) Inertial Measure Unit (IMU) and magnetic sensors and a 16-bit microcontroller. The resulting estimates are compared with a high precision motion system to demonstrate its performance. PMID:24201316

  7. A Robust Nonlinear Observer for Real-Time Attitude Estimation Using Low-Cost MEMS Inertial Sensors

    Directory of Open Access Journals (Sweden)

    Lizeth Torres

    2013-11-01

    Full Text Available This paper deals with the attitude estimation of a rigid body equipped with angular velocity sensors and reference vector sensors. A quaternion-based nonlinear observer is proposed in order to fuse all information sources and to obtain an accurate estimation of the attitude. It is shown that the observer error dynamics can be separated into two passive subsystems connected in “feedback”. Then, this property is used to show that the error dynamics is input-to-state stable when the measurement disturbance is seen as an input and the error as the state. These results allow one to affirm that the observer is “robustly stable”. The proposed observer is evaluated in real-time with the design and implementation of an Attitude and Heading Reference System (AHRS based on low-cost MEMS (Micro-Electro-Mechanical Systems Inertial Measure Unit (IMU and magnetic sensors and a 16-bit microcontroller. The resulting estimates are compared with a high precision motion system to demonstrate its performance.

  8. An adaptive fuzzy prediction model for real time tumor tracking in radiotherapy via external surrogates.

    Science.gov (United States)

    Esmaili Torshabi, Ahmad; Riboldi, Marco; Imani Fooladi, Abbas Ali; Modarres Mosalla, Seyed Mehdi; Baroni, Guido

    2013-01-07

    In the radiation treatment of moving targets with external surrogates, information on tumor position in real time can be extracted by using accurate correlation models. A fuzzy environment is proposed here to correlate input surrogate data with tumor motion estimates in real time. In this study, two different data clustering approaches were analyzed due to their substantial effects on the fuzzy modeler performance. Moreover, a comparative investigation was performed on two fuzzy-based and one neuro-fuzzy-based inference systems with respect to state-of-the-art models. Finally, due to the intrinsic interpatient variability in fuzzy models' performance, a model selectivity algorithm was proposed to select an adaptive fuzzy modeler on a case-by-case basis. The performance of multiple and adaptive fuzzy logic models were retrospectively tested in 20 patients treated with CyberKnife real-time tumor tracking. Final results show that activating adequate model selection of our fuzzy-based modeler can significantly reduce tumor tracking errors.

  9. 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.

  10. Proposing a Data Model for the Representation of Real Time Road Traffic Flow

    OpenAIRE

    Alex Alexandru SIROMASCENKO

    2011-01-01

    Given recent developments in the fields of GIS data modelling, spatial data representation and storage in spatial databases, together with wireless Internet communications, it is becoming more obvious that the requirements for developing a real time road traffic information system are being met. This paper focuses on building a data model for traffic representation with support from the current free GIS resources, open source technologies and spatial databases. Community-created GIS maps can ...

  11. New insights into the application of the Coulomb model in real-time

    OpenAIRE

    Flaminia Catalli; C.-H. Chan

    2012-01-01

    The Coulomb model for stress change estimation is considered one of the most powerful physics-based forecasting tools, even though its calculations are affected by uncertainties due to the large number of a priori assumptions needed. The aim of this paper is to suggest a straightforward and reliable strategy to apply the Coulomb model for real-time forecasting. This is done by avoiding all dispensable assumptions, thus reducing the corresponding uncertainties. We demonstrate that the depth at...

  12. 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.

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

    Science.gov (United States)

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

    2013-05-01

    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.

  14. 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.

  15. A Study on Modeling of Transmission Line in Digital Type Real-Time Power System Simulator

    Science.gov (United States)

    Yasuda, Yuji; Yokoyama, Akihiko; Tada, Yasuyuki

    In modern power systems, it is important to analyze various kindes of dynamic phenomena which appear in the system. When the effectiveness of new power electronics based apparatus, protective relay systems and etc. is tested, a real-time power system simulator is becoming a very effective tool. In general, however, it is very expensive and it is very difficult for beginners to understand how to use it. Therefore, studies on low-cost and easy-use real-time power system simulators have so far been done. We have developed models of power system components for the real-time power system simulator using DSP (Digital Signal Processor) combined with commercial CAD (Computer Aided Design) soft "MATLAB/SIMULINK". The use of commercial softwares can drastically decrease the development cost of the simulator. In this paper, a simplified reduction model of unbalanced three-phase transmission network with mutual impedance is proposed for analysis of various kinds of stability phenomena by use of the digital simulator. The proposed network model is constructed automatically and efficiently even for connection of both current source type models and voltage source type models of power apparatus such as generators, FACTS devices and loads.

  16. Modeling and Analyzing Adaptive User-Centric Systems in Real-Time Maude

    Directory of Open Access Journals (Sweden)

    Andreas Schroeder

    2010-09-01

    Full Text Available Pervasive user-centric applications are systems which are meant to sense the presence, mood, and intentions of users in order to optimize user comfort and performance. Building such applications requires not only state-of-the art techniques from artificial intelligence but also sound software engineering methods for facilitating modular design, runtime adaptation and verification of critical system requirements. In this paper we focus on high-level design and analysis, and use the algebraic rewriting language Real-Time Maude for specifying applications in a real-time setting. We propose a generic component-based approach for modeling pervasive user-centric systems and we show how to analyze and prove crucial properties of the system architecture through model checking and simulation. For proving time-dependent properties we use Metric Temporal Logic (MTL and present analysis algorithms for model checking two subclasses of MTL formulas: time-bounded response and time-bounded safety MTL formulas. The underlying idea is to extend the Real-Time Maude model with suitable clocks, to transform the MTL formulas into LTL formulas over the extended specification, and then to use the LTL model checker of Maude. It is shown that these analyses are sound and complete for maximal time sampling. The approach is illustrated by a simple adaptive advertising scenario in which an adaptive advertisement display can react to actions of the users in front of the display.

  17. Formal Verification of a Power Controller Using the Real-Time Model Checker UPPAAL

    Science.gov (United States)

    Havelund, Klaus; Larsen, Kim Guldstrand; Skou, Arne

    1999-01-01

    A real-time system for power-down control in audio/video components is modeled and verified using the real-time model checker UPPAAL. The system is supposed to reside in an audio/video component and control (read from and write to) links to neighbor audio/video components such as TV, VCR and remote-control. In particular, the system is responsible for the powering up and down of the component in between the arrival of data, and in order to do so in a safe way without loss of data, it is essential that no link interrupts are lost. Hence, a component system is a multitasking system with hard real-time requirements, and we present techniques for modeling time consumption in such a multitasked, prioritized system. The work has been carried out in a collaboration between Aalborg University and the audio/video company B&O. By modeling the system, 3 design errors were identified and corrected, and the following verification confirmed the validity of the design but also revealed the necessity for an upper limit of the interrupt frequency. The resulting design has been implemented and it is going to be incorporated as part of a new product line.

  18. 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.

  19. 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.

  20. Flexible space-based robot modelling and real-time simulation

    Science.gov (United States)

    Prins, J. J. M.; Dieleman, P.; Vanwoerkom, P. T. L. M.

    1989-11-01

    The Hermes Robot Arm (HERA) is a sophisticated space manipulator system which has to perform tasks ranging from berthing to tool operation in operational modes that range from fully automatic to purely manual. Development and qualification of such a space based manipulator must be supported by computer simulation facilities. A concise description of the HERA Simulation Facility Pilot (HSF-P) is given. It represents the first 'pilot' real-time simulation facility. Design concept, simulation models, and support tools are discussed.

  1. 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.

  2. 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.

  3. 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

  4. Active shape model-based real-time tracking of deformable objects

    Science.gov (United States)

    Kim, Sangjin; Kim, Daehee; Shin, Jeongho; Paik, Joonki

    2005-10-01

    Tracking non-rigid objects such as people in video sequences is a daunting task due to computational complexity and unpredictable environment. The analysis and interpretation of video sequence containing moving, deformable objects have been an active research areas including video tracking, computer vision, and pattern recognition. In this paper we propose a robust, model-based, real-time system to cope with background clutter and occlusion. The proposed algorithm consists of following four steps: (i) localization of an object-of-interest by analyzing four directional motions, (ii) region tracker for tracking moving region detected by the motion detector, (iii) update of training sets using the Smart Snake Algorithm (SSA) without preprocessing, (iv) active shape model-based tracking in region information. The major contribution this work lies in the integration for a completed system, which covers from image processing to tracking algorithms. The approach of combining multiple algorithms succeeds in overcoming fundamental limitations of tracking and at the same time realizes real time implementation. Experimental results show that the proposed algorithm can track people under various environment in real-time. The proposed system has potential uses in the area of surveillance, sape analysis, and model-based coding, to name of few.

  5. Computational modeling and real-time control of patient-specific laser treatment of cancer.

    Science.gov (United States)

    Fuentes, D; Oden, J T; Diller, K R; Hazle, J D; Elliott, A; Shetty, A; Stafford, R J

    2009-04-01

    An adaptive feedback control system is presented which employs a computational model of bioheat transfer in living tissue to guide, in real-time, laser treatments of prostate cancer monitored by magnetic resonance thermal imaging. The system is built on what can be referred to as cyberinfrastructure-a complex structure of high-speed network, large-scale parallel computing devices, laser optics, imaging, visualizations, inverse-analysis algorithms, mesh generation, and control systems that guide laser therapy to optimally control the ablation of cancerous tissue. The computational system has been successfully tested on in vivo, canine prostate. Over the course of an 18 min laser-induced thermal therapy performed at M.D. Anderson Cancer Center (MDACC) in Houston, Texas, the computational models were calibrated to intra-operative real-time thermal imaging treatment data and the calibrated models controlled the bioheat transfer to within 5 degrees C of the predetermined treatment plan. The computational arena is in Austin, Texas and managed at the Institute for Computational Engineering and Sciences (ICES). The system is designed to control the bioheat transfer remotely while simultaneously providing real-time remote visualization of the on-going treatment. Post-operative histology of the canine prostate reveal that the damage region was within the targeted 1.2 cm diameter treatment objective.

  6. 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.

  7. GPU-accelerated Model Checking of Periodic Self-Suspending Real-Time Tasks

    OpenAIRE

    Liberg, Tim; Måhl, Per-Erik

    2012-01-01

    Efficient model checking is important in order to make this type of software verification useful for systems that are complex in their structure. If a system is too large or complex then model checking does not simply scale, i.e., it could take too much time to verify the system. This is one strong argument for focusing on making model checking faster. Another interesting aim is to make model checking so fast that it can be used for predicting scheduling decisions for real-time schedulers at ...

  8. 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....

  9. Real-time computed tomography fluoroscopy-guided solitary lung tumor model in a rabbit.

    Directory of Open Access Journals (Sweden)

    Byeong Hyeon Choi

    Full Text Available Preclinical studies of lung cancer require suitable large-animal models to allow evaluation and development of surgical and interventional techniques. We assessed the feasibility and safety of a novel rabbit lung cancer model of solitary tumors, in which real-time computed tomography fluoroscopy is used to guide inoculation of VX2 carcinoma single-cell suspensions. Thirty-eight rabbits were divided into four groups according to the volume of the VX2 tissue or cell suspension, the volume of lipiodol, the volume of Matrigel, and the injection needle size. The mixtures were percutaneously injected into rabbit lungs under real-time computed tomography fluoroscopy guidance. Two weeks later, VX2 lung carcinomas were confirmed via positron emission tomography/computed tomography, necropsy, and histology. Real-time computed tomography fluoroscopy allowed the precise inoculation of the tumor cell suspensions containing lipiodol, while the use of Matrigel and a small needle prevented leakage of the suspensions into the lung parenchyma. Solitary lung tumors were successfully established in rabbits (n = 22 inoculated with single-cell suspensions (150 μL, lipiodol (150 μL, and Matrigel (150 μL using a 26-gauge needle. This combination was determined to be optimal. Pneumothorax was observed in only two of the 38 rabbits (5.3%, both of which survived to the end of the study without any intervention. Real-time computed tomography fluoroscopy-guided inoculation of VX2 single-cell suspensions with lipiodol and Matrigel using a small needle is an easy and safe method to establish solitary lung tumors in rabbits.

  10. Real-time computed tomography fluoroscopy-guided solitary lung tumor model in a rabbit.

    Science.gov (United States)

    Choi, Byeong Hyeon; Young, Hwan Seok; Quan, Yu Hua; Rho, Jiyun; Eo, Jae Seon; Han, Kook Nam; Choi, Young Ho; Hyun Koo, Kim

    2017-01-01

    Preclinical studies of lung cancer require suitable large-animal models to allow evaluation and development of surgical and interventional techniques. We assessed the feasibility and safety of a novel rabbit lung cancer model of solitary tumors, in which real-time computed tomography fluoroscopy is used to guide inoculation of VX2 carcinoma single-cell suspensions. Thirty-eight rabbits were divided into four groups according to the volume of the VX2 tissue or cell suspension, the volume of lipiodol, the volume of Matrigel, and the injection needle size. The mixtures were percutaneously injected into rabbit lungs under real-time computed tomography fluoroscopy guidance. Two weeks later, VX2 lung carcinomas were confirmed via positron emission tomography/computed tomography, necropsy, and histology. Real-time computed tomography fluoroscopy allowed the precise inoculation of the tumor cell suspensions containing lipiodol, while the use of Matrigel and a small needle prevented leakage of the suspensions into the lung parenchyma. Solitary lung tumors were successfully established in rabbits (n = 22) inoculated with single-cell suspensions (150 μL), lipiodol (150 μL), and Matrigel (150 μL) using a 26-gauge needle. This combination was determined to be optimal. Pneumothorax was observed in only two of the 38 rabbits (5.3%), both of which survived to the end of the study without any intervention. Real-time computed tomography fluoroscopy-guided inoculation of VX2 single-cell suspensions with lipiodol and Matrigel using a small needle is an easy and safe method to establish solitary lung tumors in rabbits.

  11. Validated real-time energy models for small-scale grid-connected PV-systems

    Energy Technology Data Exchange (ETDEWEB)

    Ayompe, L.M.; Duffy, A. [Department of Civil and Structural Engineering, School of Civil and Building Services, Dublin Institute of Technology, Bolton Street, Dublin 1 (Ireland); McCormack, S.J. [Department of Civil, Structural and Environmental Engineering, Trinity College Dublin, Dublin 2 (Ireland); Conlon, M. [School of Electrical Engineering Systems, Dublin Institute of Technology, Kevin St, Dublin 8 (Ireland)

    2010-10-15

    This paper presents validated real-time energy models for small-scale grid-connected PV-systems suitable for domestic application. The models were used to predict real-time AC power output from a PV-system in Dublin, Ireland using 30-min intervals of measured performance data between April 2009 and March 2010. Statistical analysis of the predicted results and measured data highlight possible sources of errors and the limitations and/or adequacy of existing models, to describe the temperature and efficiency of PV-cells and consequently, the accuracy of power prediction models. PV-system AC output power predictions using empirical models for PV-cell temperature and efficiency prediction showed lower percentage mean absolute errors (PMAEs) of 7.9-11.7% while non-empirical models had errors of 10.0-12.4%. Cumulative errors for PV-system AC output power predictions were 1.3% for empirical models and 3.3% for non-empirical models. The proposed models are suitable for predicting PV-system AC output power at time intervals suitable for smart metering. (author)

  12. 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.

  13. Recursive Least Squares with Real Time Stochastic Modeling: Application to GPS Relative Positioning

    Science.gov (United States)

    Zangeneh-Nejad, F.; Amiri-Simkooei, A. R.; Sharifi, M. A.; Asgari, J.

    2017-09-01

    Geodetic data processing is usually performed by the least squares (LS) adjustment method. There are two different forms for the LS adjustment, namely the batch form and recursive form. The former is not an appropriate method for real time applications in which new observations are added to the system over time. For such cases, the recursive solution is more suitable than the batch form. The LS method is also implemented in GPS data processing via two different forms. The mathematical model including both functional and stochastic models should be properly defined for both forms of the LS method. Proper choice of the stochastic model plays an important role to achieve high-precision GPS positioning. The noise characteristics of the GPS observables have been already investigated using the least squares variance component estimation (LS-VCE) in a batch form by the authors. In this contribution, we introduce a recursive procedure that provides a proper stochastic modeling for the GPS observables using the LS-VCE. It is referred to as the recursive LS-VCE (RLS-VCE) method, which is applied to the geometry-based observation model (GBOM). In this method, the (co)variances parameters can be estimated recursively when the new group of observations is added. Therefore, it can easily be implemented in real time GPS data processing. The efficacy of the method is evaluated using a real GPS data set collected by the Trimble R7 receiver over a zero baseline. The results show that the proposed method has an appropriate performance so that the estimated (co)variance parameters of the GPS observables are consistent with the batch estimates. However, using the RLS-VCE method, one can estimate the (co)variance parameters of the GPS observables when a new observation group is added. This method can thus be introduced as a reliable method for application to the real time GPS data processing.

  14. Study on Development of 1D-2D Coupled Real-time Urban Inundation Prediction model

    Science.gov (United States)

    Lee, Seungsoo

    2017-04-01

    In recent years, we are suffering abnormal weather condition due to climate change around the world. Therefore, countermeasures for flood defense are urgent task. In this research, study on development of 1D-2D coupled real-time urban inundation prediction model using predicted precipitation data based on remote sensing technology is conducted. 1 dimensional (1D) sewerage system analysis model which was introduced by Lee et al. (2015) is used to simulate inlet and overflow phenomena by interacting with surface flown as well as flows in conduits. 2 dimensional (2D) grid mesh refinement method is applied to depict road networks for effective calculation time. 2D surface model is coupled with 1D sewerage analysis model in order to consider bi-directional flow between both. Also parallel computing method, OpenMP, is applied to reduce calculation time. The model is estimated by applying to 25 August 2014 extreme rainfall event which caused severe inundation damages in Busan, Korea. Oncheoncheon basin is selected for study basin and observed radar data are assumed as predicted rainfall data. The model shows acceptable calculation speed with accuracy. Therefore it is expected that the model can be used for real-time urban inundation forecasting system to minimize damages.

  15. NONLINEAR SYSTEM MODELING USING SINGLE NEURON CASCADED NEURAL NETWORK FOR REAL-TIME APPLICATIONS

    Directory of Open Access Journals (Sweden)

    S. Himavathi

    2012-04-01

    Full Text Available Neural Networks (NN have proved its efficacy for nonlinear system modeling. NN based controllers and estimators for nonlinear systems provide promising alternatives to the conventional counterpart. However, NN models have to meet the stringent requirements on execution time for its effective use in real time applications. This requires the NN model to be structurally compact and computationally less complex. In this paper a parametric method of analysis is adopted to determine the compact and faster NN model among various neural network architectures. This work proves through analysis and examples that the Single Neuron Cascaded (SNC architecture is distinct in providing compact and simpler models requiring lower execution time. The unique structural growth of SNC architecture enables automation in design. The SNC Network is shown to combine the advantages of both single and multilayer neural network architectures. Extensive analysis on selected architectures and their models for four benchmark nonlinear theoretical plants and a practical application are tested. A performance comparison of the NN models is presented to demonstrate the superiority of the single neuron cascaded architecture for online real time applications.

  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

    2017-10-05

    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 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. Modeling and Analysis of Real-Time Database Systems in the Framework of Discrete Event Systems

    National Research Council Canada - National Science Library

    Ghosh, Anunoy

    1994-01-01

    .... Such database systems are called Real-Time Database Systems (RTDBS). The problem of concurrency control and scheduling of transactions in real time database systems is studied in the framework of discrete event dynamical systems (DEDS...

  18. 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.

  19. Real-time estimation of battery internal temperature based on a simplified thermoelectric model

    Science.gov (United States)

    Zhang, Cheng; Li, Kang; Deng, Jing

    2016-01-01

    Li-ion batteries have been widely used in the EVs, and the battery thermal management is a key but challenging part of the battery management system. For EV batteries, only the battery surface temperature can be measured in real-time. However, it is the battery internal temperature that directly affects the battery performance, and large temperature difference may exist between surface and internal temperatures, especially in high power demand applications. In this paper, an online battery internal temperature estimation method is proposed based on a novel simplified thermoelectric model. The battery thermal behaviour is first described by a simplified thermal model, and battery electrical behaviour by an electric model. Then, these two models are interrelated to capture the interactions between battery thermal and electrical behaviours, thus offer a comprehensive description of the battery behaviour that is useful for battery management. Finally, based on the developed model, the battery internal temperature is estimated using an extended Kalman filter. The experimental results confirm the efficacy of the proposed method, and it can be used for online internal temperature estimation which is a key indicator for better real-time battery thermal management.

  20. 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.

  1. 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.

  2. 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.

  3. Performance modeling and measurement of real-time multiprocessors with time-shared buses

    Science.gov (United States)

    Woodbury, Michael H.; Shin, Kang G.

    1988-01-01

    A closed queueing network model is constructed to address workload effects on computer performance for a highly reliable unibus multiprocessor used in real-time control. The queueing model consists of multiserver nodes and a nonpreemptive priority queue. Use of this model requires partitioning the workload into task classes. The time average steady-state solution of the queueing model directly produces useful results that are necessary in performance evaluation. The model is experimentally justified with the Fault-Tolerant Multiprocessor (FTMP) located at the NASA AIRLAB. Extensive experiments are performed on FTMP with a synthetic workload generator (SWG) to directly measure performance parameters, such as processor idle time, system bus contention, and task processing times. These measurements determine values for parameters in the queueing model. Experimental and analytic results are then compared.

  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. Real-time robot path planning based on a modified pulse-coupled neural network model.

    Science.gov (United States)

    Qu, Hong; Yang, Simon X; Willms, Allan R; Yi, Zhang

    2009-11-01

    This paper presents a modified pulse-coupled neural network (MPCNN) model for real-time collision-free path planning of mobile robots in nonstationary environments. The proposed neural network for robots is topologically organized with only local lateral connections among neurons. It works in dynamic environments and requires no prior knowledge of target or barrier movements. The target neuron fires first, and then the firing event spreads out, through the lateral connections among the neurons, like the propagation of a wave. Obstacles have no connections to their neighbors. Each neuron records its parent, that is, the neighbor that caused it to fire. The real-time optimal path is then the sequence of parents from the robot to the target. In a static case where the barriers and targets are stationary, this paper proves that the generated wave in the network spreads outward with travel times proportional to the linking strength among neurons. Thus, the generated path is always the global shortest path from the robot to the target. In addition, each neuron in the proposed model can propagate a firing event to its neighboring neuron without any comparing computations. The proposed model is applied to generate collision-free paths for a mobile robot to solve a maze-type problem, to circumvent concave U-shaped obstacles, and to track a moving target in an environment with varying obstacles. The effectiveness and efficiency of the proposed approach is demonstrated through simulation and comparison studies.

  7. 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

  8. Drosophila embryos as model systems for monitoring bacterial infection in real time.

    Directory of Open Access Journals (Sweden)

    Isabella Vlisidou

    2009-07-01

    Full Text Available Drosophila embryos are well studied developmental microcosms that have been used extensively as models for early development and more recently wound repair. Here we extend this work by looking at embryos as model systems for following bacterial infection in real time. We examine the behaviour of injected pathogenic (Photorhabdus asymbiotica and non-pathogenic (Escherichia coli bacteria and their interaction with embryonic hemocytes using time-lapse confocal microscopy. We find that embryonic hemocytes both recognise and phagocytose injected wild type, non-pathogenic E. coli in a Dscam independent manner, proving that embryonic hemocytes are phagocytically competent. In contrast, injection of bacterial cells of the insect pathogen Photorhabdus leads to a rapid 'freezing' phenotype of the hemocytes associated with significant rearrangement of the actin cytoskeleton. This freezing phenotype can be phenocopied by either injection of the purified insecticidal toxin Makes Caterpillars Floppy 1 (Mcf1 or by recombinant E. coli expressing the mcf1 gene. Mcf1 mediated hemocyte freezing is shibire dependent, suggesting that endocytosis is required for Mcf1 toxicity and can be modulated by dominant negative or constitutively active Rac expression, suggesting early and unexpected effects of Mcf1 on the actin cytoskeleton. Together these data show how Drosophila embryos can be used to track bacterial infection in real time and how mutant analysis can be used to genetically dissect the effects of specific bacterial virulence factors.

  9. An Alternative to Classical Real-time Magnetic Field Measurements using a Magnet Model

    CERN Document Server

    Caspers, Friedhelm; Lewis, J; Lindroos, M; Salvermoser, T

    1997-01-01

    Longitudinal and transverse beam control in circular accelerators depends critically on a reliable real-time knowledge of the magnetic bending field. Traditionally this is achieved with a long-measurement coil placed in a reference magnet. In the CERN PS Booster, such a measurement generates a 1 Gauss step-size train with an absolute precision of 0.1%. Modern magnet control can be done with a precision of 0.01%. Consequently, a synthesised magnetic field train based on a reliable magnet model could potentially yield a 10 times better result. The PSB will become a part of the injector chain for the future Large Hadron Collider (LHC). Therefore the main power supply of the PSB has been upgraded to full cycle control. This has made it possible to follow the entire magnetic cycle with a refined model, and to synthesise a real-time magnetic field train from a newly developed programmable pulse generator. We will discuss the general design concepts and the first results.

  10. Proposing a Data Model for the Representation of Real Time Road Traffic Flow

    Directory of Open Access Journals (Sweden)

    Alex Alexandru SIROMASCENKO

    2011-03-01

    Full Text Available Given recent developments in the fields of GIS data modelling, spatial data representation and storage in spatial databases, together with wireless Internet communications, it is becoming more obvious that the requirements for developing a real time road traffic information system are being met. This paper focuses on building a data model for traffic representation with support from the current free GIS resources, open source technologies and spatial databases. Community-created GIS maps can be used for easily populating an infrastructure model with accurate data; the spatial search features of relational databases can be used to map a given GPS position to the previously created network; open source ORM packages can be employed in mediating live traffic feeds into the model. A testing mechanism will be devised in order to verify the feasibility of the solution, considering performance

  11. New insights into the application of the Coulomb model in real-time

    Science.gov (United States)

    Catalli, Flaminia; Chan, Chung-Han

    2012-02-01

    The Coulomb model for stress change estimation is considered one of the most powerful physics-based forecasting tools, even though its calculations are affected by uncertainties due to the large number of a priori assumptions needed. The aim of this paper is to suggest a straightforward and reliable strategy to apply the Coulomb model for real-time forecasting. This is done by avoiding all dispensable assumptions, thus reducing the corresponding uncertainties. We demonstrate that the depth at which calculations are made is a parameter of utmost importance and apply the Coulomb model to three sequences in different tectonic regimes: Umbria-Marche (normal), Landers (strike-slip), and Chi-Chi (thrust). In each case the results confirm that when applying the Coulomb model: (i) the depth of calculation plays a fundamental role; (ii) depth uncertainties are not negligible; (iii) the best forecast at a given location is obtained by selecting the maximum stress change over the whole seismogenic depth range.

  12. Dynamic Flow Model for Real-Time Application in Wind Farm Control

    Science.gov (United States)

    Rott, Andreas; Boersma, Sjoerd; van Wingerden, Jan-Willem; Kühn, Martin

    2017-05-01

    For short-term power predictions and estimations of the available power during curtailment of a wind farm, it is necessary to consider the flow dynamics and aerodynamic interactions of the turbines. In this paper, a control-oriented dynamic two-dimensional wind farm model is introduced that aims to incorporate real-time measurements such as flow velocities at turbine locations to estimate the ambient wind farm flow. The model is intended to derive flow predictions for real-time applications. Since fully resolved computational fluid dynamics are too CPU-intensive for such a task, the dynamic model presented in this paper relies on an approximation of the flow equations in a two-dimensional framework. A semi-Lagrangian advection scheme and a step-wise flow solver together offer fast calculation speed, which scales linearly with the number of grid points. In order to emulate effects of realistic three-dimensional wind farm flow, a relaxation of the two-dimensional continuity equation is presented. Furthermore, with little extra computational expense, additional dynamic state variables for various possible applications can be propagated along the wind flow. For instance, a dynamic confidence parameter can provide estimations of the accuracy of flow predictions, while a turbulence parameter adds the possibility to estimate wake induced loads on downstream turbines. In order to demonstrate the performance and validity of the new model it is compared with other models. At first a two turbine reference case is compared with a steady-state model and secondly with results obtained by the dynamic wind farm flow model WFSim. Finally a small wind farm is simulated in order to show the computational scaling of the model.

  13. 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.

  14. Quantitative mitral valve modeling using real-time three-dimensional echocardiography: technique and repeatability.

    Science.gov (United States)

    Jassar, Arminder Singh; Brinster, Clayton J; Vergnat, Mathieu; Robb, J Daniel; Eperjesi, Thomas J; Pouch, Alison M; Cheung, Albert T; Weiss, Stuart J; Acker, Michael A; Gorman, Joseph H; Gorman, Robert C; Jackson, Benjamin M

    2011-01-01

    Real-time three-dimensional (3D) echocardiography has the ability to construct quantitative models of the mitral valve (MV). Imaging and modeling algorithms rely on operator interpretation of raw images and may be subject to observer-dependent variability. We describe a comprehensive analysis technique to generate high-resolution 3D MV models and examine interoperator and intraoperator repeatability in humans. Patients with normal MVs were imaged using intraoperative transesophageal real-time 3D echocardiography. The annulus and leaflets were manually segmented using a TomTec Echo-View workstation. The resultant annular and leaflet point cloud was used to generate fully quantitative 3D MV models using custom Matlab algorithms. Eight images were subjected to analysis by two independent observers. Two sequential images were acquired for 6 patients and analyzed by the same observer. Each pair of annular tracings was compared with respect to conventional variables and by calculating the mean absolute distance between paired renderings. To compare leaflets, MV models were aligned so as to minimize their sum of squares difference, and their mean absolute difference was measured. Mean absolute annular and leaflet distance was 2.4±0.8 and 0.6±0.2 mm for the interobserver and 1.5±0.6 and 0.5±0.2 mm for the intraobserver comparisons, respectively. There was less than 10% variation in annular variables between comparisons. These techniques generate high-resolution, quantitative 3D models of the MV and can be used consistently to image the human MV with very small interoperator and intraoperator variability. These data lay the framework for reliable and comprehensive noninvasive modeling of the normal and diseased MV. Copyright © 2011 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

  15. 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.

  16. Near real time weather and ocean model data access with rNOMADS

    Science.gov (United States)

    Bowman, D. C.; Lees, J. M.

    2015-05-01

    The National Oceanic and Atmospheric Administration Operational Model Archive and Distribution System (NOMADS) facilitates rapid delivery of real time and archived atmospheric and oceanic model outputs from multiple agencies. These data are free to the scientific community, industry, and the public. The rNOMADS package provides an interface between NOMADS and the R programming language. Like R itself, rNOMADS is open source and cross platform. It utilizes server-side functionality on the NOMADS system to subset model outputs for delivery to client R users. We discuss rNOMADS implementation and usage as well as provide two case studies. Users can download rNOMADS from within the R interpreter or from the Comprehensive R Archive Network (CRAN).

  17. 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.

  18. Real-Time Gait Event Detection Based on Kinematic Data Coupled to a Biomechanical Model.

    Science.gov (United States)

    Lambrecht, Stefan; Harutyunyan, Anna; Tanghe, Kevin; Afschrift, Maarten; De Schutter, Joris; Jonkers, Ilse

    2017-03-24

    Real-time detection of multiple stance events, more specifically initial contact (IC), foot flat (FF), heel off (HO), and toe off (TO), could greatly benefit neurorobotic (NR) and neuroprosthetic (NP) control. Three real-time threshold-based algorithms have been developed, detecting the aforementioned events based on kinematic data in combination with a biomechanical model. Data from seven subjects walking at three speeds on an instrumented treadmill were used to validate the presented algorithms, accumulating to a total of 558 steps. The reference for the gait events was obtained using marker and force plate data. All algorithms had excellent precision and no false positives were observed. Timing delays of the presented algorithms were similar to current state-of-the-art algorithms for the detection of IC and TO, whereas smaller delays were achieved for the detection of FF. Our results indicate that, based on their high precision and low delays, these algorithms can be used for the control of an NR/NP, with the exception of the HO event. Kinematic data is used in most NR/NP control schemes and is thus available at no additional cost, resulting in a minimal computational burden. The presented methods can also be applied for screening pathological gait or gait analysis in general in/outside of the laboratory.

  19. 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.

  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. A New Statistical Model of Electroencephalogram Noise Spectra for Real-Time Brain-Computer Interfaces.

    Science.gov (United States)

    Paris, Alan; Atia, George K; Vosoughi, Azadeh; Berman, Stephen A

    2017-08-01

    A characteristic of neurological signal processing is high levels of noise from subcellular ion channels up to whole-brain processes. In this paper, we propose a new model of electroencephalogram (EEG) background periodograms, based on a family of functions which we call generalized van der Ziel-McWhorter (GVZM) power spectral densities (PSDs). To the best of our knowledge, the GVZM PSD function is the only EEG noise model that has relatively few parameters, matches recorded EEG PSD's with high accuracy from 0 to over 30 Hz, and has approximately 1/fθ behavior in the midfrequencies without infinities. We validate this model using three approaches. First, we show how GVZM PSDs can arise in a population of ion channels at maximum entropy equilibrium. Second, we present a class of mixed autoregressive models, which simulate brain background noise and whose periodograms are asymptotic to the GVZM PSD. Third, we present two real-time estimation algorithms for steady-state visual evoked potential (SSVEP) frequencies, and analyze their performance statistically. In pairwise comparisons, the GVZM-based algorithms showed statistically significant accuracy improvement over two well-known and widely used SSVEP estimators. The GVZM noise model can be a useful and reliable technique for EEG signal processing. Understanding EEG noise is essential for EEG-based neurology and applications such as real-time brain-computer interfaces, which must make accurate control decisions from very short data epochs. The GVZM approach represents a successful new paradigm for understanding and managing this neurological noise.

  2. Real-time ecohydrological modelling in the Elbe river basin to assess the current weather trend

    Science.gov (United States)

    Roers, Michael; Wechsung, Frank; Gottschalk, Pia; Rachimow, Claus; Conradt, Tobias

    2013-04-01

    The ecohydrological model SWIM (Soil and Water Integrated Model) was applied to the German part of the Elbe River basin on a day-to-day basis using real-time data from 19 weather stations. An available parameterised version of the model was used, which was calibrated and validated in previous studies considering the runoff at the basin outlet and various interior stations. In this study, the range of analysed model outputs was extended to soil water dynamics, plant growth and yields. To evaluate these outputs, a validation study was conducted on different spatial scales. The data used for validation includes runoff, yield and evapotranspiration data, each corresponding to a specific spatial scale. The simulated runoff at the basin outlet and subbasin outlets was validated using gauge data, simulated crop yield was validated on basin and subbasin scale with yield data that was available for administrative districts. Lysimeter measurements were used to validate percolation, evapotranspiration rates and crop yield. The results for the runoff at basin scale are satisfactory, while there are discrepancies between the simulated and observed runoff of the Havel and Saale subbasins, due to modification of the runoff regime by hydrological management. The simulated yield is in agreement with observations on basin and subbasin scale. The inter-annual fluctuation, however, could not always be reproduced adequately. On the field scale, the comparison of the simulated yield with the lysimeter data shows a good fit. The monthly aggregated values of evapotranspiration rates and percolation water, that differ between soil types, exhibit some mismatches, especially in Loess soil. Apart from these deviations, the model performed well at the different scales and is capable of providing real-time simulations at watershed-, subbasin- and field scale. Since it integrates hydrology, soil water dynamics and plant growth, it provides useful information, e. g. the development of the soil

  3. 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.

  4. A graphical user interface for real-time spectroscopy: software architecture for data collection, feature extraction, model development, and real-time testing

    Science.gov (United States)

    Torrione, Peter; Morton, Kenneth, Jr.; Lunsford, Chris; Collins, Leslie

    2009-05-01

    Recent advances in Laser-Induced breakdown spectroscopy (LIBS), Raman spectroscopy, and other spectroscopic approaches have increased interest in the application of spectroscopy to detection of explosives along with other chemical-signature identification tasks. However most existing spectroscopic data collection techniques require manual interaction with data files including data manipulation using multiple pieces of software and different file formats, time-consuming feature-selection, and model re-generation. Not only do these steps reduce analytic efficiency and slow the progress of research in spectroscopy, but they also inhibit real-time use of the systems by end-users. In this work we present a graphical user interface designed to increase efficiency for spectroscopic data collection, feature selection, classifier development, and testing. We present a software architecture that provides enough flexibility to handle data from many different spectroscopic sensors. We also discuss feature-level and model-level software components that allow for the features and classification approaches to be manipulated interactively, and we present a simple and intuitive testing screen suitable for an end user to make decisions in the field with out requiring a "human in the loop" for processing.

  5. Novel mouse hemostasis model for real-time determination of bleeding time and hemostatic plug composition

    Science.gov (United States)

    GETZ, T. M.; PIATT, R.; PETRICH, B. G.; MONROE, D.; MACKMAN, N.; BERGMEIER, W.

    2015-01-01

    Summary Introduction Hemostasis is a rapid response by the body to stop bleeding at sites of vessel injury. Both platelets and fibrin are important for the formation of a hemostatic plug. Mice have been used to uncover the molecular mechanisms that regulate the activation of platelets and coagulation under physiologic conditions. However, measurements of hemostasis in mice are quite variable, and current methods do not quantify platelet adhesion or fibrin formation at the site of injury. Methods We describe a novel hemostasis model that uses intravital fluorescence microscopy to quantify platelet adhesion, fibrin formation and time to hemostatic plug formation in real time. Repeated vessel injuries of ~ 50–100 μm in diameter were induced with laser ablation technology in the saphenous vein of mice. Results Hemostasis in this model was strongly impaired in mice deficient in glycoprotein Ibα or talin-1, which are important regulators of platelet adhesiveness. In contrast, the time to hemostatic plug formation was only minimally affected in mice deficient in the extrinsic tissue factor (TFlow) or the intrinsic factor IX coagulation pathways, even though platelet adhesion was significantly reduced. A partial reduction in platelet adhesiveness obtained with clopidogrel led to instability within the hemostatic plug, especially when combined with impaired coagulation in TFlow mice. Conclusions In summary, we present a novel, highly sensitive method to quantify hemostatic plug formation in mice. On the basis of its sensitivity to platelet adhesion defects and its real-time imaging capability, we propose this model as an ideal tool with which to study the efficacy and safety of antiplatelet agents. PMID:25442192

  6. 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 (HRnet). 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 HRnet, 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Ghosh, Soumen [Department; Andersen, Amity [Environmental; Gagliardi, Laura [Department; Cramer, Christopher J. [Department; Govind, Niranjan [Environmental

    2017-08-16

    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-visible spectra of medium-sized systems like P3B2, f-coronene, and in addition much larger systems like 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 indeed often quantitatively accurate results when compared with RT- TDDFT or experimental spectra. While demonstrated here for INDO/S in particular, our implementation provides a framework for performing electron dynamics in large systems using semiempirical Hartree-Fock (HF) Hamiltonians in general.

  8. 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.

  9. The NIST Real-Time Control System (RCS): A Reference Model Architecture for Computational Intelligence

    Science.gov (United States)

    Albus, James S.

    1996-01-01

    The Real-time Control System (RCS) developed at NIST and elsewhere over the past two decades defines a reference model architecture for design and analysis of complex intelligent control systems. The RCS architecture consists of a hierarchically layered set of functional processing modules connected by a network of communication pathways. The primary distinguishing feature of the layers is the bandwidth of the control loops. The characteristic bandwidth of each level is determined by the spatial and temporal integration window of filters, the temporal frequency of signals and events, the spatial frequency of patterns, and the planning horizon and granularity of the planners that operate at each level. At each level, tasks are decomposed into sequential subtasks, to be performed by cooperating sets of subordinate agents. At each level, signals from sensors are filtered and correlated with spatial and temporal features that are relevant to the control function being implemented at that level.

  10. AERIS - applications for the environment : real-time information synthesis : eco-lanes operational scenario modeling report.

    Science.gov (United States)

    2014-12-01

    This report constitutes the detailed modeling and evaluation results of the Eco-Lanes Operational Scenario : defined by the Applications for the Environment: Real-Time Information Synthesis (AERIS) Program. The : Operational Scenario constitutes six ...

  11. 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.

  12. Developing Near Real-time Data-assimilative Models and Tools for the Space Environment Project

    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)...

  13. 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.

  14. Retracking CryoSat waveforms for near-real-time ocean forecast products, platform attitude, and other applications

    Science.gov (United States)

    Smith, W. H.; Scharroo, R.; Lillibridge, J. L.; Leuliette, E. W.

    2011-12-01

    The SIRAL altimeter on CryoSat, launched in 2010, can operate in three modes: the low-rate mode (LRM) behaves as a conventional altimeter; the SAR mode allows more precise range and more focused footprint through use of synthetic aperture radar (SAR), also known as delay-Doppler, processing; the SARIN mode, or interferometric SAR, also affords across-track slope determination from interferometry. We have been working on several CryoSat studies over this year and will present some highlights. For the conventional LRM mode, we have built a retracker that processes near-real-time (FDM: Fast Delivery Mode) and Level 1-B data at 20 Hz to yield wind speed, wave height, and sea surface height anomaly. These data are being fed to NOAA's National Centers for Environmental Prediction. The retracking also estimates the off-nadir mispointing angle of the satellite. After accounting for an effect due to orbit height variations, we find that the off-nadir angle estimates are sufficiently accurate that we have used them to calibrate biases in the pitch and roll of the spacecraft platform reported by the platform attitude control system. These biases account for mis-alignment between the star tracker bench and the antenna boresight. We have Full Bit Rate (FBR) data in SAR mode for some ocean passes, including portions crossing coastlines, both from ocean to land and from land to ocean. FBR data includes all the raw I and Q samples of the raw radar echoes, prior to the range FFT that deramps the chirp, or the azimuth FFT that initiates the delay-Doppler SAR focusing calculation. We are currently working on these data with several applications in mind: (1) We can use these data to trace exactly what happens as the instrument crosses a coastline. (2) We can use these data to derive a LRM (conventional) waveform as well as a SAR waveform, and can compare the performance of these two modes under the same conditions (sea state, propagation, etc.) (3) We can test a conjecture by J R

  15. 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.

  16. 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.

  17. Real time forecasts through physical and stochastic models of earthquake clustering

    Science.gov (United States)

    Murru, M.; Console, R.; Catalli, F.; Falcone, G.

    2005-12-01

    The phenomenon of earthquake interaction has become a popular subject of study because it can shed light on the physical processes leading to earthquakes, and because it has a potential value for short-term earthquake forecast and hazard mitigation. In this study we start from a purely stochastic approach known as the so-called epidemic model (ETAS) introduced by Ogata in 1988 and its variations. Then we build up an approach by which this model and the rate-and-state constitutive law introduced by Dieterich in the `90s have been merged in a single algorithm and statistically tested. Tests on real seismicity and comparison with a plain time-independent Poissonian model through likelihood-based methods have reliably proved their validity. The models are suitable for real-time forecast of the seismic activity. In the context of the low-magnitude Italian seismicity recorded from 1987 to 2005, the new model incorporating the physical concept of the rate-and-state theory performs not better than the purely stochastic model. Nevertheless, it has the advantage of needing a smaller number of free parameters and providing new interesting insights on the physics of the seismogenic process.

  18. 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.

  19. Effects of Real-Time NASA Vegetation Data on Model Forecasts of Severe Weather

    Science.gov (United States)

    Case, Jonathan L.; Bell, Jordan R.; LaFontaine, Frank J.; Peters-Lidard, Christa D.

    2012-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA-EOS Aqua and Terra satellites. NASA SPoRT started generating daily real-time GVF composites at 1-km resolution over the Continental United States beginning 1 June 2010. A companion poster presentation (Bell et al.) primarily focuses on impact results in an offline configuration of the Noah land surface model (LSM) for the 2010 warm season, comparing the SPoRT/MODIS GVF dataset to the current operational monthly climatology GVF available within the National Centers for Environmental Prediction (NCEP) and Weather Research and Forecasting (WRF) models. This paper/presentation primarily focuses on individual case studies of severe weather events to determine the impacts and possible improvements by using the real-time, high-resolution SPoRT-MODIS GVFs in place of the coarser-resolution NCEP climatological GVFs in model simulations. The NASA-Unified WRF (NU-WRF) modeling system is employed to conduct the sensitivity simulations of individual events. The NU-WRF is an integrated modeling system based on the Advanced Research WRF dynamical core that is designed to represents aerosol, cloud, precipitation, and land processes at satellite-resolved scales in a coupled simulation environment. For this experiment, the coupling between the NASA Land Information System (LIS) and the WRF model is utilized to measure the impacts of the daily SPoRT/MODIS versus the monthly NCEP climatology GVFs. First, a spin-up run of the LIS is integrated for two years using the Noah LSM to ensure that the land surface fields reach an equilibrium state on the 4-km grid mesh used. Next, the spin-up LIS is run in two separate modes beginning on 1 June 2010, one continuing with the climatology GVFs while the

  20. Real-time model based process monitoring of enzymatic biodiesel production.

    Science.gov (United States)

    Price, Jason; Nordblad, Mathias; Woodley, John M; Huusom, Jakob K

    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 × 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 the model and the process data for all of the five measured components (triglycerides, diglycerides, monoglycerides, fatty acid methyl esters, and free fatty acid). The most significant reduction for the three process runs, were for the monoglyceride and free fatty acid concentration. For those components, 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, given the infrequent and sometimes uncertain measurements obtained we see the use of the Continuous-Discrete Extended Kalman Filter as a viable tool for real time process monitoring. © 2014 American Institute of Chemical Engineers.

  1. 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...

  2. A search for model parsimony in a real time flood forecasting system

    Science.gov (United States)

    Grossi, G.; Balistrocchi, M.

    2009-04-01

    As regards the hydrological simulation of flood events, a physically based distributed approach is the most appealing one, especially in those areas where the spatial variability of the soil hydraulic properties as well as of the meteorological forcing cannot be left apart, such as in mountainous regions. On the other hand, dealing with real time flood forecasting systems, less detailed models requiring a minor number of parameters may be more convenient, reducing both the computational costs and the calibration uncertainty. In fact in this case a precise quantification of the entire hydrograph pattern is not necessary, while the expected output of a real time flood forecasting system is just an estimate of the peak discharge, the time to peak and in some cases the flood volume. In this perspective a parsimonious model has to be found in order to increase the efficiency of the system. A suitable case study was identified in the northern Apennines: the Taro river is a right tributary to the Po river and drains about 2000 km2 of mountains, hills and floodplain, equally distributed . The hydrometeorological monitoring of this medium sized watershed is managed by ARPA Emilia Romagna through a dense network of uptodate gauges (about 30 rain gauges and 10 hydrometers). Detailed maps of the surface elevation, land use and soil texture characteristics are also available. Five flood events were recorded by the new monitoring network in the years 2003-2007: during these events the peak discharge was higher than 1000 m3/s, which is actually quite a high value when compared to the mean discharge rate of about 30 m3/s. The rainfall spatial patterns of such storms were analyzed in previous works by means of geostatistical tools and a typical semivariogram was defined, with the aim of establishing a typical storm structure leading to flood events in the Taro river. The available information was implemented into a distributed flood event model with a spatial resolution of 90m

  3. Real-time inversions for finite fault slip models and rupture geometry based on high-rate GPS data

    Science.gov (United States)

    Minson, Sarah E.; Murray, Jessica R.; Langbein, John O.; Gomberg, Joan S.

    2015-01-01

    We present an inversion strategy capable of using real-time high-rate GPS data to simultaneously solve for a distributed slip model and fault geometry in real time as a rupture unfolds. We employ Bayesian inference to find the optimal fault geometry and the distribution of possible slip models for that geometry using a simple analytical solution. By adopting an analytical Bayesian approach, we can solve this complex inversion problem (including calculating the uncertainties on our results) in real time. Furthermore, since the joint inversion for distributed slip and fault geometry can be computed in real time, the time required to obtain a source model of the earthquake does not depend on the computational cost. Instead, the time required is controlled by the duration of the rupture and the time required for information to propagate from the source to the receivers. We apply our modeling approach, called Bayesian Evidence-based Fault Orientation and Real-time Earthquake Slip, to the 2011 Tohoku-oki earthquake, 2003 Tokachi-oki earthquake, and a simulated Hayward fault earthquake. In all three cases, the inversion recovers the magnitude, spatial distribution of slip, and fault geometry in real time. Since our inversion relies on static offsets estimated from real-time high-rate GPS data, we also present performance tests of various approaches to estimating quasi-static offsets in real time. We find that the raw high-rate time series are the best data to use for determining the moment magnitude of the event, but slightly smoothing the raw time series helps stabilize the inversion for fault geometry.

  4. Oregon Washington Coastal Ocean Forecast System: Real-time Modeling and Data Assimilation

    Science.gov (United States)

    Erofeeva, S.; Kurapov, A. L.; Pasmans, I.

    2016-02-01

    Three-day forecasts of ocean currents, temperature and salinity along the Oregon and Washington coasts are produced daily by a numerical ROMS-based ocean circulation model. NAM is used to derive atmospheric forcing for the model. Fresh water discharge from Columbia River, Fraser River, and small rivers in Puget Sound are included. The forecast is constrained by open boundary conditions derived from the global Navy HYCOM model and once in 3 days assimilation of recent data, including HF radar surface currents, sea surface temperature from the GOES satellite, and SSH from several satellite altimetry missions. 4-dimensional variational data assimilation is implemented in 3-day time windows using the tangent linear and adjoint codes developed at OSU. The system is semi-autonomous - all the data, including NAM and HYCOM fields are automatically updated, and daily operational forecast is automatically initiated. The pre-assimilation data quality control and post-assimilation forecast quality control require the operator's involvement. The daily forecast and 60 days of hindcast fields are available for public on opendap. As part of the system model validation plots to various satellites and SEAGLIDER are also automatically updated and available on the web (http://ingria.coas.oregonstate.edu/rtdavow/). Lessons learned in this pilot real-time coastal ocean forecasting project help develop and test metrics for forecast skill assessment for the West Coast Operational Forecast System (WCOFS), currently at testing and development phase at the National Oceanic and Atmospheric Administration (NOAA).

  5. 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.

  6. 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. PMID:28046074

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

    Directory of Open Access Journals (Sweden)

    A. Y. Babeyko

    2010-07-01

    Full Text Available 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. Pairwise Force SPH Model for Real-Time Multi-Interaction Applications.

    Science.gov (United States)

    Yang, Tao; Martin, Ralph R; Lin, Ming C; Chang, Jian; Hu, Shi-Min

    2017-10-01

    In this paper, we present a novel pairwise-force smoothed particle hydrodynamics (PF-SPH) model to enable simulation of various interactions at interfaces in real time. Realistic capture of interactions at interfaces is a challenging problem for SPH-based simulations, especially for scenarios involving multiple interactions at different interfaces. Our PF-SPH model can readily handle multiple types of interactions simultaneously in a single simulation; its basis is to use a larger support radius than that used in standard SPH. We adopt a novel anisotropic filtering term to further improve the performance of interaction forces. The proposed model is stable; furthermore, it avoids the particle clustering problem which commonly occurs at the free surface. We show how our model can be used to capture various interactions. We also consider the close connection between droplets and bubbles, and show how to animate bubbles rising in liquid as well as bubbles in air. Our method is versatile, physically plausible and easy-to-implement. Examples are provided to demonstrate the capabilities and effectiveness of our approach.

  9. Real-time mid-wavelength infrared scene rendering with a feasible BRDF model

    Science.gov (United States)

    Wu, Xin; Zhang, Jianqi; Chen, Yang; Huang, Xi

    2015-01-01

    Practically modeling and rendering the surface-leaving radiance of large-scale scenes in mid-wavelength infrared (MWIR) is an important feature of Battlefield Environment Simulation (BES). Since radiation transfer in realistic scenes is complex, it is difficult to develop real-time simulations directly from first principle. Nevertheless, it is crucial to minimize distortions in the rendering of virtual scenes. This paper proposes a feasible bidirectional reflectance distribution function (BRDF) model to deal with a large-scale scene in the MWIR band. Our BRDF model is spectrally dependent and evolved from previous BRDFs, and meets both Helmholtz reciprocity and energy conservation. We employ our BRDF model to calculate the direct solar and sky contributions. Both of them are added to the surface thermal emission in order to give the surface-leaving radiance. Atmospheric path radiance and transmission are pre-calculated to speed up the programming for rendering large scale scenes. Quantitative and qualitative comparisons with MWIR field data are made to assess the render results of our proposed method.

  10. Hydraulic Modeling and Evolutionary Optimization for Enhanced Real-Time Decision Support of Combined Sewer Overflows

    Science.gov (United States)

    Zimmer, A. L.; Minsker, B. S.; Schmidt, A. R.; Ostfeld, A.

    2011-12-01

    Real-time mitigation of combined sewer overflows (CSOs) requires evaluation of multiple operational strategies during rapidly changing rainfall events. Simulation models for hydraulically complex systems can effectively provide decision support for short time intervals when coupled with efficient optimization. This work seeks to reduce CSOs for a test case roughly based on the North Branch of the Chicago Tunnel and Reservoir Plan (TARP), which is operated by the Metropolitan Water Reclamation District of Greater Chicago (MWRDGC). The North Branch tunnel flows to a junction with the main TARP system. The Chicago combined sewer system alleviates potential CSOs by directing high interceptor flows through sluice gates and dropshafts to a deep tunnel. Decision variables to control CSOs consist of sluice gate positions that control water flow to the tunnel as well as a treatment plant pumping rate that lowers interceptor water levels. A physics-based numerical model is used to simulate the hydraulic effects of changes in the decision variables. The numerical model is step-wise steady and conserves water mass and momentum at each time step by iterating through a series of look-up tables. The look-up tables are constructed offline to avoid extensive real-time calculations, and describe conduit storage and water elevations as a function of flow. A genetic algorithm (GA) is used to minimize CSOs at each time interval within a moving horizon framework. Decision variables are coded at 15-minute increments and GA solutions are two hours in duration. At each 15-minute interval, the algorithm identifies a good solution for a two-hour rainfall forecast. Three GA modifications help reduce optimization time. The first adjustment reduces the search alphabet by eliminating sluice gate positions that do not influence overflow volume. The second GA retains knowledge of the best decision at the previous interval by shifting the genes in the best previous sequence to initialize search at

  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. Real-Time Flood Forecasting System Using Channel Flow Routing Model with Updating by Particle Filter

    Science.gov (United States)

    Kudo, R.; Chikamori, H.; Nagai, A.

    2008-12-01

    A real-time flood forecasting system using channel flow routing model was developed for runoff forecasting at water gauged and ungaged points along river channels. The system is based on a flood runoff model composed of upstream part models, tributary part models and downstream part models. The upstream part models and tributary part models are lumped rainfall-runoff models, and the downstream part models consist of a lumped rainfall-runoff model for hillslopes adjacent to a river channel and a kinematic flow routing model for a river channel. The flow forecast of this model is updated by Particle filtering of the downstream part model as well as by the extended Kalman filtering of the upstream part model and the tributary part models. The Particle filtering is a simple and powerful updating algorithm for non-linear and non-gaussian system, so that it can be easily applied to the downstream part model without complicated linearization. The presented flood runoff model has an advantage in simlecity of updating procedure to the grid-based distributed models, which is because of less number of state variables. This system was applied to the Gono-kawa River Basin in Japan, and flood forecasting accuracy of the system with both Particle filtering and extended Kalman filtering and that of the system with only extended Kalman filtering were compared. In this study, water gauging stations in the objective basin were divided into two types of stations, that is, reference stations and verification stations. Reference stations ware regarded as ordinary water gauging stations and observed data at these stations are used for calibration and updating of the model. Verification stations ware considered as ungaged or arbitrary points and observed data at these stations are used not for calibration nor updating but for only evaluation of forecasting accuracy. The result confirms that Particle filtering of the downstream part model improves forecasting accuracy of runoff at

  14. 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.

  15. Efficient real-time path integrals for non-Markovian spin-boson models

    Science.gov (United States)

    Strathearn, A.; Lovett, B. W.; Kirton, P.

    2017-09-01

    Strong coupling between a system and its environment leads to the emergence of non-Markovian dynamics, which cannot be described by a time-local master equation. One way to capture such dynamics is to use numerical real-time path integrals, where assuming a finite bath memory time enables manageable simulation scaling. However, by comparing to the exactly soluble independent boson model, we show that the presence of transient negative decay rates in the exact dynamics can result in simulations with unphysical exponential growth of density matrix elements when the finite memory approximation is used. We therefore reformulate this approximation in such a way that the exact dynamics are reproduced identically and then apply our new method to the spin-boson model with superohmic environmental coupling, commonly used to model phonon environments, but which cannot be solved exactly. Our new method allows us to easily access parameter regimes where we find revivals in population dynamics which are due to non-Markovian backflow of information from the bath to the system.

  16. Modelling effluent quality based on a real-time optical monitoring of the wastewater treatment process.

    Science.gov (United States)

    Tomperi, Jani; Koivuranta, Elisa; Kuokkanen, Anna; Leiviskä, Kauko

    2017-01-01

    A novel optical monitoring device was used for imaging an activated sludge process in situ during a period of over one year. In this study, the dependencies between the results of image analysis and the process measurements were studied, and the optical monitoring results were utilized to predict the important quality parameters for the wastewater treatment process efficiency: suspended solids, biological oxygen demand, chemical oxygen demand, total nitrogen and total phosphorous in biologically treated wastewater. The optimal subsets of variables for each model were searched using five variable selection methods. It was shown that online optical analysis results have clear dependencies on some process variables and the purification result. The model based on optical monitoring and process variables from the early stage of the treatment process can be used to predict the levels of important quality parameters, and to show the quality of the biologically treated wastewater hours in advance. This study confirms that the optical monitoring method is a valuable tool for monitoring a wastewater treatment process and receiving new information in real time. Combined with predictive modelling, it has the potential to be used in process control, keeping the process in a stable operating condition and avoiding environmental risks.

  17. Near Real-Time Probabilistic Damage Diagnosis Using Surrogate Modeling and High Performance Computing

    Science.gov (United States)

    Warner, James E.; Zubair, Mohammad; Ranjan, Desh

    2017-01-01

    This work investigates novel approaches to probabilistic damage diagnosis that utilize surrogate modeling and high performance computing (HPC) to achieve substantial computational speedup. Motivated by Digital Twin, a structural health management (SHM) paradigm that integrates vehicle-specific characteristics with continual in-situ damage diagnosis and prognosis, the methods studied herein yield near real-time damage assessments that could enable monitoring of a vehicle's health while it is operating (i.e. online SHM). High-fidelity modeling and uncertainty quantification (UQ), both critical to Digital Twin, are incorporated using finite element method simulations and Bayesian inference, respectively. The crux of the proposed Bayesian diagnosis methods, however, is the reformulation of the numerical sampling algorithms (e.g. Markov chain Monte Carlo) used to generate the resulting probabilistic damage estimates. To this end, three distinct methods are demonstrated for rapid sampling that utilize surrogate modeling and exploit various degrees of parallelism for leveraging HPC. The accuracy and computational efficiency of the methods are compared on the problem of strain-based crack identification in thin plates. While each approach has inherent problem-specific strengths and weaknesses, all approaches are shown to provide accurate probabilistic damage diagnoses and several orders of magnitude computational speedup relative to a baseline Bayesian diagnosis implementation.

  18. Salish Sea Nowcast: A Real-time High-Resolution Model for Forecasts and Research Support

    Science.gov (United States)

    Latornell, D.; Allen, S. E.; Soontiens, N. K.; Dunn, M. B. H.; Liu, J.; Machuca, I.

    2016-02-01

    The Salish Sea real-time model system produces two forecasts and a nowcast daily, providing storm surge forecasts for several municipality stakeholders.Without human intervention, the automation system collects the required forcing data from various web services, runs the model and publishes results in the form of plots on several web pages.Here we will present the automation framework that enables a research model to be run operationally.The automation runs across two computer systems with a cloud computing facility running the numerical model (NEMO in our case), and a local Linux server doing everything else.The system has a modular, asynchronous architecture that is coordinated by a messaging framework.A manager process coordinates the sequencing and operation of a collection of worker processes each responsible for a specific task in the preparation for a model run, execution of the run, analysis, visualization, and publication to the web of the run results.Techniques that make the system reasonably fault tolerant will be discussed.The modular design easily allows researchers with a variety of skill sets to contribute to the framework to the benefit of the project and its knowledge transfer to stakeholders.We will discuss the performance of the system during the 2014-2016 storm surge seasons,and routine evaluation against sea surface height observation data streams.Daily model runs with best available weather and river runoff forcing facilitate continuous evaluation against cabled observatory data streams.We will show how those evaluations provide important insights that help to driveresearch that improves the model.

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

    Science.gov (United States)

    Ruf, Boitumelo; Schuchert, Tobias

    2016-10-01

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

  1. REAL-TIME SIMULATIVE MODELING FOR GEAR CHANGE CONTROL STRATEGY RESEARCH

    Directory of Open Access Journals (Sweden)

    A. A. Filimonov

    2009-01-01

    Full Text Available The paper deals with an efficiency estimation of automated mechanical transmission at off-line simulation stage. A simulation model of a vehicle with an automated power unit for gear change control strategy research has been developed in the paper. The paper contains a complex mathematical description of the analysis scheme. It allows adequately to react to structure reorganization and parameter change of the dynamic system at an application of external disturbances from the road and a driver. A peculiar feature of the developed software that is an opportunity of real-time modeling. This decision enables to estimate automated mechanical transmission operation at a wide spectrum of the driver’s actions. The experiment on a driving simulation of a heavy truck with 40000 kg GCW on a road climb has been carried out. The estimated values of driving on a route have been compared  during gear changes in automatic and command modes by drivers of various qualification. The paper contains conclusions about efficiency of the analyzed gear change control strategy. A strategy for improvement of automated mechanical transmission controlling algorithms has been proposed in the paper.

  2. 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...

  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. A Real-Time Non-invasive Auto-bioluminescent Urinary Bladder Cancer Xenograft Model.

    Science.gov (United States)

    John, Bincy Anu; Xu, Tingting; Ripp, Steven; Wang, Hwa-Chain Robert

    2017-02-01

    The study was to develop an auto-bioluminescent urinary bladder cancer (UBC) xenograft animal model for pre-clinical research. The study used a humanized, bacteria-originated lux reporter system consisting of six (luxCDABEfrp) genes to express components required for producing bioluminescent signals in human UBC J82, J82-Ras, and SW780 cells without exogenous substrates. Immune-deficient nude mice were inoculated with Lux-expressing UBC cells to develop auto-bioluminescent xenograft tumors that were monitored by imaging and physical examination. Lux-expressing auto-bioluminescent J82-Lux, J82-Ras-Lux, and SW780-Lux cell lines were established. Xenograft tumors derived from tumorigenic Lux-expressing auto-bioluminescent J82-Ras-Lux cells allowed a serial, non-invasive, real-time monitoring by imaging of tumor development prior to the presence of palpable tumors in animals. Using Lux-expressing auto-bioluminescent tumorigenic cells enabled us to monitor the entire course of xenograft tumor development through tumor cell implantation, adaptation, and growth to visible/palpable tumors in animals.

  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. 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.

  7. 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...

  8. Real-time Application of the Multihazard Hurricane Impact Level Model for the Atlantic Basin

    Directory of Open Access Journals (Sweden)

    Stephanie F. Pilkington

    2017-11-01

    Full Text Available Tropical cyclones are an example of a multihazard event with impacts that can highly vary depending on landfall location, wind speed, storm surge, and inland flooding from precipitation. These storms are typically categorized by their wind speed and pressure, while evacuation orders are typically given based on storm surge. The general public relies on these single hazard assessment parameters when attempting to understand the risk of an oncoming event. However, after the fact, these events are ranked by economic damage and death toll. Therefore, it is imperative that when these events are communicated to the public, during the forecast period, the multiple hazards are incorporated in terms the public can easily associate with, such as economic damage. This article provides an evaluation of the potential for real-time use of artificial neural networks, through the utilization of an already developed Hurricane Impact Level (HIL Model, to forecast a range of economic damage from tropical cyclone events, during the 2015 and 2016 United States hurricane season. The HIL Model is built prior to the start of each season and simulated every 3 h, in conjunction with National Hurricane Center (NHC issued advisories, for oncoming tropical cyclones forecasted to make landfall. Weaker and more common tropical cyclones have a less varied forecast and produce more accurate impact level (IL predictions. More complicated and uncertain events, such as 2016 Hurricane Matthew, require the user’s discretion in communicating varying landfall locations for a complex track forecast to the model. As NHC forecasts change with respect to both track and meteorological hazards affecting land, the estimated IL and the HIL model confidence will also change. In other words, if a track shifts to a more vulnerable location, or to more locations, or the meteorological hazards increase, the IL will subsequently increase. All tropical cyclones from the 2015 and 2016 seasons

  9. Numerical modelling for real-time forecasting of marine oil pollution and hazard assessment

    Science.gov (United States)

    De Dominicis, Michela; Pinardi, Nadia; Bruciaferri, Diego; Liubartseva, Svitlana

    2015-04-01

    (MEDESS4MS) system, which is an integrated operational multi-model oil spill prediction service, that can be used by different users to run simulations of oil spills at sea, even in real time, through a web portal. The MEDESS4MS system gathers different oil spill modelling systems and data from meteorological and ocean forecasting systems, as well as operational information on response equipment, together with environmental and socio-economic sensitivity maps. MEDSLIK-II has been also used to provide an assessment of hazard stemming from operational oil ship discharges in the Southern Adriatic and Northern Ionian (SANI) Seas. Operational pollution resulting from ships consists of a movable hazard with a magnitude that changes dynamically as a result of a number of external parameters varying in space and time (temperature, wind, sea currents). Simulations of oil releases have been performed with realistic oceanographic currents and the results show that the oil pollution hazard distribution has an inherent spatial and temporal variability related to the specific flow field variability.

  10. 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.

  11. 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

  12. Predictive modeling of respiratory tumor motion for real-time prediction of baseline shifts

    Science.gov (United States)

    Balasubramanian, A.; Shamsuddin, R.; Prabhakaran, B.; Sawant, A.

    2017-03-01

    Baseline shifts in respiratory patterns can result in significant spatiotemporal changes in patient anatomy (compared to that captured during simulation), in turn, causing geometric and dosimetric errors in the administration of thoracic and abdominal radiotherapy. We propose predictive modeling of the tumor motion trajectories for predicting a baseline shift ahead of its occurrence. The key idea is to use the features of the tumor motion trajectory over a 1 min window, and predict the occurrence of a baseline shift in the 5 s that immediately follow (lookahead window). In this study, we explored a preliminary trend-based analysis with multi-class annotations as well as a more focused binary classification analysis. In both analyses, a number of different inter-fraction and intra-fraction training strategies were studied, both offline as well as online, along with data sufficiency and skew compensation for class imbalances. The performance of different training strategies were compared across multiple machine learning classification algorithms, including nearest neighbor, Naïve Bayes, linear discriminant and ensemble Adaboost. The prediction performance is evaluated using metrics such as accuracy, precision, recall and the area under the curve (AUC) for repeater operating characteristics curve. The key results of the trend-based analysis indicate that (i) intra-fraction training strategies achieve highest prediction accuracies (90.5-91.4%) (ii) the predictive modeling yields lowest accuracies (50-60%) when the training data does not include any information from the test patient; (iii) the prediction latencies are as low as a few hundred milliseconds, and thus conducive for real-time prediction. The binary classification performance is promising, indicated by high AUCs (0.96-0.98). It also confirms the utility of prior data from previous patients, and also the necessity of training the classifier on some initial data from the new patient for reasonable

  13. Validation of Real-time Modeling of Coronal Mass Ejections Using the WSA-ENLIL+Cone Heliospheric Model

    Science.gov (United States)

    Romano, M.; Mays, M. L.; Taktakishvili, A.; MacNeice, P. J.; Zheng, Y.; Pulkkinen, A. A.; Kuznetsova, M. M.; Odstrcil, D.

    2013-12-01

    Modeling coronal mass ejections (CMEs) is of great interest to the space weather research and forecasting communities. We present recent validation work of real-time CME arrival time predictions at different satellites using the WSA-ENLIL+Cone three-dimensional MHD heliospheric model available at the Community Coordinated Modeling Center (CCMC) and performed by the Space Weather Research Center (SWRC). SWRC is an in-house research-based operations team at the CCMC which provides interplanetary space weather forecasting for NASA's robotic missions and performs real-time model validation. The quality of model operation is evaluated by comparing its output to a measurable parameter of interest such as the CME arrival time and geomagnetic storm strength. The Kp index is calculated from the relation given in Newell et al. (2007), using solar wind parameters predicted by the WSA-ENLIL+Cone model at Earth. The CME arrival time error is defined as the difference between the predicted arrival time and the observed in-situ CME shock arrival time at the ACE, STEREO A, or STEREO B spacecraft. This study includes all real-time WSA-ENLIL+Cone model simulations performed between June 2011-2013 (over 400 runs) at the CCMC/SWRC. We report hit, miss, false alarm, and correct rejection statistics for all three spacecraft. For hits we show the average absolute CME arrival time error, and the dependence of this error on CME input parameters such as speed, width, and direction. We also present the predicted geomagnetic storm strength (using the Kp index) error for Earth-directed CMEs.

  14. An Integrated Modeling and Observing System with Near Real-Time Applications

    Science.gov (United States)

    Kafatos, M.; El-Askary, H. M.; Galanis, G.; Hatzopoulos, N.; Liu, X.; Ouzounov, D. P.; Prasad, A. K.; Tremback, C.

    2010-12-01

    A number of advanced systems in computing and observations have been installed at Chapman and are either operational or under advanced development. At Chapman University, we have acquired our own Direct Broadcast XL satellite antenna system which observes the Western United States with near real-time capabilities. With the direct-broadcast antenna we will be able to receive and analyze n near real time NASA Moderate Resolution Imaging Spectroradiometer (MODIS) data from Terra and Aqua satellites, data from MetOp, NOAA POES, and from FY1D (China) satellites. The MODIS sensor simultaneously monitors land, sea and atmosphere with 1km resolution. The data are broadcast on X-band and are being received at Chapman starting in August 2010. There are no operational restrictions to the use of MODIS data and significantly, the sensors will be followed by similar instruments providing a continuity of observations through future operational systems until 2018. These characteristics make MODIS attractive for operational monitoring applications and this presentation describes the design and implementation of a near-real time system to process visible and thermal data from MODIS Terra and Aqua. We also plan to access AIRS on Aqua data. The new satellite receiving station will advance the research and teaching activities in Earth systems science, by demonstrating how satellite technology changes the way we study the Earth .The polar-orbiting satellite data received at Chapman University will support new science development in remote sensing, disaster management and information monitoring systems. The near real-time polar-orbiting satellite data can help to solve real-world environmental problems and to advance the environmental forecasting and regional decision-making. Specific applications will be discussed.

  15. Control-oriented modeling and real-time control for the ozone dosing process of drinking water treatment.

    Science.gov (United States)

    Wang, Dongsheng; Li, Shihua; Zhou, Xingpeng

    2013-03-05

    Ozonation is one of the most important steps during drinking water treatment. To improve the efficiency of ozonation and to stabilize the quality of the treated water, control-oriented modeling and a real-time control method for the ozone dosing process are developed in this study. Compared with existing ozonation models developed by bench-scale and pilot-scale batch experiments, the model reported herein is control-oriented and based on plant-scale batch experiments. A real-time control strategy for maintaining a constant ozone exposure is attempted to meet primary disinfection requirements. An internal model control scheme is proposed to maintain a constant ozone exposure by adjusting the ozone dosage. The proposed real-time control method can cope with changing water quality, water flow rate, and process operational conditions. Both simulations and experimental studies have been carried out and implemented for the ozone dosing process control system, and the results demonstrate the effectiveness and practicality of this real-time control method.

  16. 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,

  17. Real-Time Global Flood Estimation Using Satellite-Based Precipitation and a Coupled Land Surface and Routing Model

    Science.gov (United States)

    Wu, Huan; Adler, Robert F.; Tian, Yudong; Huffman, George J.; Li, Hongyi; Wang, JianJian

    2014-01-01

    A widely used land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing-based runoff-routing model to form the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model, which serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS uses real-time satellite-based precipitation to derive flood monitoring parameters for the latitude band 50 deg. N - 50 deg. S at relatively high spatial (approximately 12 km) and temporal (3 hourly) resolution. Examples of model results for recent flood events are computed using the real-time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS, the DRIVE model is run retrospectively for 15 years using both research-quality and real-time satellite precipitation products. Evaluation results are slightly better for the research-quality input and significantly better for longer duration events (3 day events versus 1 day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is approximately 0.9 and the false alarm ratio is approximately 0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1121 river gauges across the quasi-global domain. Validation using real-time precipitation across the tropics (30 deg. S - 30 deg. N) gives positive daily Nash-Sutcliffe Coefficients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. There were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.

  18. Multi-scale Evaluation of a Real Time Multi-satellite Precipitation Forced Global Hydrological Modeling System

    Science.gov (United States)

    Zhang, Y.; Hong, Y.; Gao, H.; Xue, X.; Gourley, J. J.

    2013-12-01

    A Global Hydrological Modeling System (GHMS), with its core part of a physical based distributed hydrological model called Coupled Routing and Excess STorage (CREST), has been established and applied for real time global flood monitoring thus providing early warning for decision makers and stakeholders. The updated Version 7 Near Real Time TRMM Multi-satellite Precipitation Analysis (TRMM-RT) with the potential to apply for real time flood prediction without gauge adjustment especially beneficial to those regions sparsely covered by gauge networks, was used to force the CREST model with the spatial resolution of 1/8 degree from 50N to 50S quasi-globally (http://eos.ou.edu) for a retrospective period (2002-2012). The simulated hydrological variables (e.g. runoff depth and streamflow) were compared with Global Runoff Data Center (GRDC) observations in terms of gridded global runoff climatology (mm/yr), the selected basins based annual mean and seasonality of streamflow prediction, daily and monthly scale based streamflow prediction skills over different continents, etc. At global scale, the TRMM RT derived gridded global runoff climatology (mm/yr) and model simulated annual streamflow mean over selected basins are in general agreement with GRDC observation, though with performance variation over different continents (e.g. Africa shows relatively poorer performance due to the sparsely in-situ networks for TMPA RT algorithm development). The results also indicate that the modeling performance is better with a larger basin size and a location near the equator. Given the global availability of satellite-based precipitation in near real-time, this study demonstrates the opportunities and challenges that exist for the real time flood prediction on basis of GHMS, which is particularly useful for the vast ungauged regions of the globe.

  19. The characteristics of the real-time land surface emissivity of the ATMS data for numerical weather prediction model

    Science.gov (United States)

    Kim, Jisoo; Ahn, Myoung-Hwan; Kim, Eunjin

    2017-04-01

    An accurate estimation of land surface emissivity in the microwave region is essential to expand the utilization of microwave satellite observations to the data assimilation process of numerical weather prediction (NWP) scheme. Several attempts have been made to derive real-time emissivities for this purpose. Here, we try to characterize the real-time land surface emissivity derived from the Advanced Technology Microwave Sounder (ATMS) data with auxiliary information obtained from the radiative simulation; RTTOV-11.2 with the Unified Model of the Korea Meteorological Administration's operational NWP model. Comparison of the real-time emissivities with a climatological emissivity atlas, TELSEM (A Tool to Estimate Land Surface Emissivities at Microwave frequencies), shows a significant improvement in the first guess departure; the reduced bias with the increased number of observations that pass the quality control along with the decreased diurnal variation of the first guess departure. Further, the uncertainty of the real-time emissivities has been estimated over the desert and dense forest areas where the physical variables related to the emissivity are relatively stable. With the 15 days of data at the selected target area, the estimated uncertainty varies about 0.5-5% (1.5-15 K) over both regions. The suspected error sources are the errors inherent in auxiliary data (e.g. surface temperature or temperature and humidity profiles) or the imperfect cloud screening which will be further analyzed.

  20. Estimation of Low Quantity Genes: A Hierarchical Model for Analyzing Censored Quantitative Real-Time PCR Data

    OpenAIRE

    Boyer, Tim C.; Tim Hanson; Singer, Randall S.

    2013-01-01

    Analysis of gene quantities measured by quantitative real-time PCR (qPCR) can be complicated by observations that are below the limit of quantification (LOQ) of the assay. A hierarchical model estimated using MCMC methods was developed to analyze qPCR data of genes with observations that fall below the LOQ (censored observations). Simulated datasets with moderate to very high levels of censoring were used to assess the performance of the model; model results were compared to approaches that r...

  1. Using SCADA Data, Field Studies, and Real-Time Modeling to Calibrate Flint's Hydraulic Model

    Science.gov (United States)

    EPA has been providing technical assistance to the City of Flint and the State of Michigan in response to the drinking water lead contamination incident. Responders quickly recognized the need for a water distribution system hydraulic model to provide insight on flow patterns an...

  2. Integrated modeling of storm drain and natural channel networks for real-time flash flood forecasting in large urban areas

    Science.gov (United States)

    Habibi, H.; Norouzi, A.; Habib, A.; Seo, D. J.

    2016-12-01

    To produce accurate predictions of flooding in urban areas, it is necessary to model both natural channel and storm drain networks. While there exist many urban hydraulic models of varying sophistication, most of them are not practical for real-time application for large urban areas. On the other hand, most distributed hydrologic models developed for real-time applications lack the ability to explicitly simulate storm drains. In this work, we develop a storm drain model that can be coupled with distributed hydrologic models such as the National Weather Service Hydrology Laboratory's Distributed Hydrologic Model, for real-time flash flood prediction in large urban areas to improve prediction and to advance the understanding of integrated response of natural channels and storm drains to rainfall events of varying magnitude and spatiotemporal extent in urban catchments of varying sizes. The initial study area is the Johnson Creek Catchment (40.1 km2) in the City of Arlington, TX. For observed rainfall, the high-resolution (500 m, 1 min) precipitation data from the Dallas-Fort Worth Demonstration Network of the Collaborative Adaptive Sensing of the Atmosphere radars is used.

  3. A novel application of real-time RT-LAMP for body fluid identification: using HBB detection as the model.

    Science.gov (United States)

    Su, Chih-Wen; Li, Chiao-Yun; Lee, James Chun-I; Ji, Dar-Der; Li, Shu-Ying; Daniel, Barbara; Syndercombe-Court, Denise; Linacre, Adrian; Hsieh, Hsing-Mei

    2015-06-01

    We report on a novel application of real-time reverse transcription-loop-mediated isothermal amplification (real-time RT-LAMP) to identify the presence of a specific body fluid using blood as a proof-of-concept model. By comparison with recently developed methods of body fluid identification, the RT-LAMP assay is rapid and requires only one simple heating-block maintained at a single temperature, circumventing the need for dedicated equipment. RNA was extracted from different body fluids (blood, semen, saliva, menstrual blood, sweat, and urine) for use in real-time RT-LAMP reaction. The 18S rRNA locus was used as the internal control and hemoglobin beta (HBB) as the blood-specific marker. Reverse transcription and LAMP reaction were performed in the same tube using a turbidimeter for real-time monitoring the reaction products within a threshold of 60 min. HBB LAMP products were only detected in blood and not in any of the other body fluid, but products from the 18S rRNA gene were detected in all the tested body fluids as expected. The limit of detection was a minimum of 10(-5) ng total RNA for detection of both 18S rRNA and HBB. Augmenting the detection of RT-LAMP products was performed by separation of the products using gel electrophoresis and collecting the fluorescence of calcein. The data collected indicated complete concordance with the body fluid tested regardless of the method of detection used. This is the first application of real-time RT-LAMP to detect body fluid specific RNA and indicates the use of this method in forensic biology.

  4. 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.

  5. 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.

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

    Science.gov (United States)

    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&M) method which addresses the sensor modeling and algorithms issues. A physical sensor model for ICM&M is derived based on interference optics utilizing the concept of instantaneous frequency. The associated calibration procedure is outlined for ICM&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&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.

  7. 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.

  8. Development of a New Research Platform for Electrical Drive System Modelling for Real-Time Digital Simulation Applications

    Directory of Open Access Journals (Sweden)

    S. Umashankar

    2013-01-01

    Full Text Available This paper presents the research platform for real-time digital simulation applications which replaces the requirement for full-scale or partial-scale validation of physical systems. To illustrate this, a three-phase AC-DC-AC converter topology has been used consists of diode rectifier, DC link, and an IGBT inverter with inductive load. In this topology, rectifier as well as inverter decoupled and solved separately using decoupled method, which results in the reduced order system so that it is easy to solve the state equation. This method utilizes an analytical approach to formulate the state equations, and interpolation methods have been implemented to rectify the zero-crossing errors, with fixed step size of 100 μsec is used. The proposed algorithm and the model have been validated using MATLAB simulation as m-file program and also in real-time DSP controller domain. The performance of the real-time system model is evaluated based on accuracy, zero crossing, and step size.

  9. Simulation Evaluation of Pilot Inputs for Real Time Modeling During Commercial Flight Operations

    Science.gov (United States)

    Martos, Borja; Ranaudo, Richard; Oltman, Ryan; Myhre, Nick

    2017-01-01

    Aircraft dynamics characteristics can only be identified from flight data when the aircraft dynamics are excited sufficiently. A preliminary study was conducted into what types and levels of manual piloted control excitation would be required for accurate Real-Time Parameter IDentification (RTPID) results by commercial airline pilots. This includes assessing the practicality for the pilot to provide this excitation when cued, and to further understand if pilot inputs during various phases of flight provide sufficient excitation naturally. An operationally representative task was evaluated by 5 commercial airline pilots using the NASA Ice Contamination Effects Flight Training Device (ICEFTD). Results showed that it is practical to use manual pilot inputs only as a means of achieving good RTPID in all phases of flight and in flight turbulence conditions. All pilots were effective in satisfying excitation requirements when cued. Much of the time, cueing was not even necessary, as just performing the required task provided enough excitation for accurate RTPID estimation. Pilot opinion surveys reported that the additional control inputs required when prompted by the excitation cueing were easy to make, quickly mastered, and required minimal training.

  10. Computer optimization techniques for NASA Langley's CSI evolutionary model's real-time control system

    Science.gov (United States)

    Elliott, Kenny B.; Ugoletti, Roberto; Sulla, Jeff

    1992-01-01

    The evolution and optimization of a real-time digital control system is presented. The control system is part of a testbed used to perform focused technology research on the interactions of spacecraft platform and instrument controllers with the flexible-body dynamics of the platform and platform appendages. The control system consists of Computer Automated Measurement and Control (CAMAC) standard data acquisition equipment interfaced to a workstation computer. The goal of this work is to optimize the control system's performance to support controls research using controllers with up to 50 states and frame rates above 200 Hz. The original system could support a 16-state controller operating at a rate of 150 Hz. By using simple yet effective software improvements, Input/Output (I/O) latencies and contention problems are reduced or eliminated in the control system. The final configuration can support a 16-state controller operating at 475 Hz. Effectively the control system's performance was increased by a factor of 3.

  11. 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.

  12. Infusion-line pressure as a real-time monitor of convection-enhanced delivery in pre-clinical models.

    Science.gov (United States)

    Lam, Miu Fei; Foo, Stacy W L; Thomas, Meghan G; Lind, Christopher R P

    2014-01-15

    Acute convection-enhanced delivery (CED) is a neurosurgical delivery technique that allows for precise and uniform distribution of an infusate to a brain structure. It remains experimental due to difficulties in ensuring successful delivery. Real-time monitoring is able to provide immediate feedback on cannula placement, infusate distribution, and if the infusion is proceeding as planned or is failing due to reflux or catheter obstruction. Pressure gradient is the driving force behind CED, with the infusion pressure being directly proportional to the flow-rate. The aim of this study was to assess the feasibility of using infusion-line pressure profiling to distinguish in real-time between succeeding and failing CED infusions. To do so we delivered cresyl violet dye at 0.5, 1.0 and 2.0 μl/min via CED in vitro using 0.6% agarose gel and in vivo to the rat striatum. Infusions that failed in agarose gel models could only be differentiated late during the procedures. In the rat in vivo model, the infusion-line profiles of obstructed infusions were not distinctive from those of successful infusions. Intraoperative magnetic resonance imaging (MRI) is used for real-time visualisation of cannula placement and infusate distribution. Particularly for animal pre-clinical work, it would be advantageous to supplement MRI with a cheap, accessible technique to monitor infusions and provide a real-time measure of infusion success or failure. Infusion-line pressure monitoring was of limited value in identifying successful CED with small volume infusions, whilst its utility for large volume infusion remains unknown. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

  13. A Real-Time Model-Based Human Motion Tracking and Analysis for Human-Computer Interface Systems

    Directory of Open Access Journals (Sweden)

    Chung-Lin Huang

    2004-09-01

    Full Text Available This paper introduces a real-time model-based human motion tracking and analysis method for human computer interface (HCI. This method tracks and analyzes the human motion from two orthogonal views without using any markers. The motion parameters are estimated by pattern matching between the extracted human silhouette and the human model. First, the human silhouette is extracted and then the body definition parameters (BDPs can be obtained. Second, the body animation parameters (BAPs are estimated by a hierarchical tritree overlapping searching algorithm. To verify the performance of our method, we demonstrate different human posture sequences and use hidden Markov model (HMM for posture recognition testing.

  14. 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.

  15. 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

    2014-05-14

    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. 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.

  17. An integrated approach for real-time model-based state-of-charge estimation of lithium-ion batteries

    Science.gov (United States)

    Zhang, Cheng; Li, Kang; Pei, Lei; Zhu, Chunbo

    2015-06-01

    Lithium-ion batteries have been widely adopted in electric vehicles (EVs), and accurate state of charge (SOC) estimation is of paramount importance for the EV battery management system. Though a number of methods have been proposed, the SOC estimation for Lithium-ion batteries, such as LiFePo4 battery, however, faces two key challenges: the flat open circuit voltage (OCV) vs SOC relationship for some SOC ranges and the hysteresis effect. To address these problems, an integrated approach for real-time model-based SOC estimation of Lithium-ion batteries is proposed in this paper. Firstly, an auto-regression model is adopted to reproduce the battery terminal behaviour, combined with a non-linear complementary model to capture the hysteresis effect. The model parameters, including linear parameters and non-linear parameters, are optimized off-line using a hybrid optimization method that combines a meta-heuristic method (i.e., the teaching learning based optimization method) and the least square method. Secondly, using the trained model, two real-time model-based SOC estimation methods are presented, one based on the real-time battery OCV regression model achieved through weighted recursive least square method, and the other based on the state estimation using the extended Kalman filter method (EKF). To tackle the problem caused by the flat OCV-vs-SOC segments when the OCV-based SOC estimation method is adopted, a method combining the coulombic counting and the OCV-based method is proposed. Finally, modelling results and SOC estimation results are presented and analysed using the data collected from LiFePo4 battery cell. The results confirmed the effectiveness of the proposed approach, in particular the joint-EKF method.

  18. Real Time Speed Control of a DC Motor Based on its Integer and Non-Integer Models Using PWM Signal

    Directory of Open Access Journals (Sweden)

    A. W. Nasir

    2017-10-01

    Full Text Available This paper exploits the advantage of non-integer order modeling of a process over integer order, in those cases where the process model is required for control purpose. The present case deals with speed control of a DC motor. Based on the real time open loop response, DC motor is being modeled as integer and non-integer order first order plus delay system. Both these models are then separately used for determining two sets of Proportional-Integral-Derivative (PID controller parameters through Ziegler Nichols (ZN closed loop tuning method. In addition to this, a model based control technique i.e. Internal Model Control (IMC is also implemented using both integer and non-integer model respectively. For carrying out the real time speed control of DC motor, LabVIEW platform has been used. After going through the results, it is observed that the controller performance considerably improves, if non-integer order model is used for controller design rather than integer order model.

  19. 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

  20. 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.

  1. Tracing Temporal Changes of Model Parameters in Rainfall-Runoff Modeling via a Real-Time Data Assimilation

    Directory of Open Access Journals (Sweden)

    Shanshan Meng

    2016-01-01

    Full Text Available Watershed characteristics such as patterns of land use and land cover (LULC, soil structure and river systems, have substantially changed due to natural and anthropogenic factors. To adapt hydrological models to the changing characteristics of watersheds, one of the feasible strategies is to explicitly estimate the changed parameters. However, few approaches have been dedicated to these non-stationary conditions. In this study, we employ an ensemble Kalman filter (EnKF technique with a constrained parameter evolution scheme to trace the parameter changes. This technique is coupled to a rainfall-runoff model, i.e., the Xinanjiang (XAJ model. In addition to a stationary condition, we designed three typical non-stationary conditions, including sudden, gradual and rotational changes with respect to two behavioral parameters of the XAJ. Synthetic experiments demonstrated that the EnKF-based method can trace the three types of parameter changes in real time. This method shows robust performance even for the scenarios of high-level uncertainties within rainfall input, modeling and observations, and it holds an implication for detecting changes in watershed characteristics. Coupling this method with a rainfall-runoff model is useful to adapt the model to non-stationary conditions, thereby improving flood simulations and predictions.

  2. 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.

  3. Initializing the WRF Model with Tropical Cyclone Real-Time Reports Using the Ensemble Kalman Filter Algorithm

    Science.gov (United States)

    Du, Tien Duc; Ngo-Duc, Thanh; Kieu, Chanh

    2017-07-01

    This study presents an approach to assimilate tropical cyclone (TC) real-time reports and the University of Wisconsin-Cooperative Institute for Meteorological Satellite Studies (CIMSS) Atmospheric Motion Vectors (AMV) data into the Weather Research and Forecasting (WRF) model for TC forecast applications. Unlike current methods in which TC real-time reports are used to either generate a bogus vortex or spin up a model initial vortex, the proposed approach ingests the TC real-time reports through blending a dynamically consistent synthetic vortex structure with the CIMSS-AMV data. The blended dataset is then assimilated into the WRF initial condition, using the local ensemble transform Kalman filter (LETKF) algorithm. Retrospective experiments for a number of TC cases in the northwestern Pacific basin during 2013-2014 demonstrate that this approach could effectively increase both the TC circulation and enhance the large-scale environment that the TCs are embedded in. Further evaluation of track and intensity forecast errors shows that track forecasts benefit more from improvement in the large-scale flow at 4-5-day lead times, whereas the intensity improvement is minimal. While the difference between the track and intensity improvement could be due to a specific model configuration, this result appears to be consistent with the recent reports of insignificant impacts of inner core data assimilation in operational TC models at the long range of 4-5 days. The new approach will be most beneficial for future regional TC models that are directly initialized from very high-resolution global models whose storm initial locations are sufficiently accurate at the initial analysis that there is no need to carry out any artificial vortex removal or filtering steps.

  4. 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.

  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...... satisfactory predictions for the smaller catchment but rather large uncertainties for the bigger catchment where the applied storage cascade seems too simple. Radar rainfall introduces more uncertainty into the flow forecast model estimation. However, the radar rainfall forecasts also result in a slightly...

  6. A C++ framework for active objects in embedded real-time systems-bridging the gap between modeling and implementation

    DEFF Research Database (Denmark)

    Caspersen, Michael Edelgaard

    1999-01-01

    for this is that the predominant object-oriented programming language in industry, C++, does not support concurrency. In this paper we present a simple and powerful approach to extending C++ with constructs for concurrent programming. We discuss the design, application, and implementation of a framework that supports standard...... concurrency constructs and, contrary to what is suggested in several books on object oriented modeling techniques for real-time systems, we demonstrate that it is possible to integrate the notions of object and process and maintain a smooth-virtually non-existing-transition from modeling to implementation...

  7. 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.

  8. 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...

  9. Minerva neural network based surrogate model for real time inference of ion temperature profiles at Wendelstein 7-X

    Science.gov (United States)

    Pavone, Andrea; Svensson, Jakob; Langenberg, Andreas; Pablant, Novimir; Wolf, Robert C.

    2017-10-01

    Artificial neural networks (ANNs) can reduce the computation time required for the application of Bayesian inference on large amounts of data by several orders of magnitude, making real-time analysis possible and, at the same time, providing a reliable alternative to more conventional inversion routines. The large scale fusion experiment Wendelstein 7-X (W7-X) requires tens of diagnostics for plasma parameter measurements and is using the Minerva Bayesian modelling framework as its main inference engine, which can handle joint inference in complex systems made of several physics models. Conventional inversion routines are applied to measured data to infer the posterior distribution of the free parameters of the models implemented in the framework. We have trained ANNs on a training set made of samples from the prior distribution of the free parameters and the corresponding data calculated with the forward model, so that the trained ANNs constitute a surrogate model of the physics model. The ANNs have been then applied to 2D images measured by an X-ray spectrometer, representing the spectral emission from plasma impurities measured along a fan of lines of sight covering a major fraction of the plasma cross-section, for the inference of ion temperature profiles and then compared with the conventional inversion routines, showing that they constitute a robust and reliable alternative for real time plasma parameter inference.

  10. Goat Model for Direct Visualizing the Effectiveness of Detaching Sinus Mucosa in Real Time During Crestal Maxillary Sinus Floor Elevation.

    Science.gov (United States)

    Fan, Jiadong; Hu, Pin; Li, Yanfeng; Wang, Fuli; Dong, Xinming; Liu, Bin; Liu, Le; Zhang, Yue; Gu, Xiangmin

    2017-08-01

    The procedure of crestal maxillary sinus floor elevation presents a great challenge to the field of implant dentistry. Due to the limited visualization in this procedure, the effectiveness of detaching sinus mucosa could not be assessed in real time. We recently developed an ex vivo goat sinus model by cutting the goat residual skulls along four lines determined from computerized tomography (CT) scans, extracting the maxillary premolar or molar teeth, and preparing implant socket in the maxilla. The generated ex vivo goat sinus models exposed the maxilla and the whole maxillary sinus mucosa, thus enabling real-time observation of detaching maxillary sinus mucosa via directly visualizing the working situation of sinus lift tool in the models and directly measuring the length of detached mucosa and space volume generated under the elevated sinus mucosa. One commercially available umbrella-shaped sinus lift curette was used to detach the maxillary sinus mucosa to evaluate the effectiveness of the ex vivo goat sinus models. The results showed that this curette could detach the sinus mucosa 3.75 mm in length in the mesiodistal direction and 2.81 mm in the buccal-palatal direction. Moreover, a space volume of 52.7 μl could be created under the elevated sinus mucosa in the goat ex vivo models. All the experimental results suggested that this ex vivo goat sinus model might be useful in the evaluation of improved or newly designed sinus lift tools for elevating the maxillary sinus mucosa via the crestal approach.

  11. Modeling Real-Time Coordination of Distributed Expertise and Event Response in NASA Mission Control Center Operations

    Science.gov (United States)

    Onken, Jeffrey

    This dissertation introduces a multidisciplinary framework for the enabling of future research and analysis of alternatives for control centers for real-time operations of safety-critical systems. The multidisciplinary framework integrates functional and computational models that describe the dynamics in fundamental concepts of previously disparate engineering and psychology research disciplines, such as group performance and processes, supervisory control, situation awareness, events and delays, and expertise. The application in this dissertation is the real-time operations within the NASA Mission Control Center in Houston, TX. This dissertation operationalizes the framework into a model and simulation, which simulates the functional and computational models in the framework according to user-configured scenarios for a NASA human-spaceflight mission. The model and simulation generates data according to the effectiveness of the mission-control team in supporting the completion of mission objectives and detecting, isolating, and recovering from anomalies. Accompanying the multidisciplinary framework is a proof of concept, which demonstrates the feasibility of such a framework. The proof of concept demonstrates that variability occurs where expected based on the models. The proof of concept also demonstrates that the data generated from the model and simulation is useful for analyzing and comparing MCC configuration alternatives because an investigator can give a diverse set of scenarios to the simulation and the output compared in detail to inform decisions about the effect of MCC configurations on mission operations performance.

  12. Comparison of Germanium Bipolar Junction Transistor Models for Real-Time Circuit Simulation

    OpenAIRE

    Holmes, Ben; Holters, Martin; van Walstijn, Maarten

    2017-01-01

    The Ebers-Moll model has been widely used to represent Bipolar Junction Transistors (BJTs) in Virtual Analogue (VA) circuits. An investigation into the validity of this model is presented in which the Ebers-Moll model is compared to BJT models of higher complexity , introducing the Gummel-Poon model to the VA field. A comparison is performed using two complementary approaches: on fit to measurements taken directly from BJTs, and on application to physical circuit models. Targeted parameter ex...

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

    Science.gov (United States)

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

    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.

  14. 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

  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

    the original semantics of PACOR and enables the verification of PACOR systems using symbolic model checking in UPPAAL and statistical model checking UPPAAL SMC. Finally we provide an example to illustrate system specification in PACOR, translation and verification....

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

    Indian Academy of Sciences (India)

    NCMRWF), India. Simple ensemble mean (EMN) giving equal weight to member models, bias-corrected ensemble mean (BCEMn) and MME forecast, where different weights are given to member models, are the products of the algorithm tested here.

  17. 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....

  18. Real-Time Perceptual Model for Distraction in Interfering Audio-on-Audio Scenarios

    DEFF Research Database (Denmark)

    Rämö, Jussi; Bech, Søren; Jensen, Søren Holdt

    2017-01-01

    was to utilize similar features as the previous model, but to use faster underlying algorithms to calculate these features. The results show that the proposed model has a root mean squared error of 11.9%, compared to the previous model's 11.0%, while only taking 0.04% of the computational time of the previous...

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

    DEFF Research Database (Denmark)

    Mikkelsen, T.; Desiato, F.

    1993-01-01

    considerations, model performance and evaluation records, computational needs, user expertise, and type of sources to be modelled. Models suitable for a given accident scenario are chosen from this hierarchy in order to provide the dose assessments via the dispersion module. A forecasting feasibility...

  20. 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.

  1. Real-time muscle deformation via decoupled modeling of solid and muscle fiber mechanics.

    Science.gov (United States)

    Berranen, Yacine; Hayashibe, Mitsuhiro; Guiraud, David; Gilles, Benjamin

    2014-01-01

    This paper presents a novel approach for simulating 3D muscle deformations with complex architectures. The approach consists in choosing the best model formulation in terms of computation cost and accuracy, that mixes a volumetric-tissue model based on finite element method (3D FEM), a muscle fiber model (Hill contractile 1D element) and a membrane model accounting for aponeurosis tissue (2D FEM). The separate models are mechanically binded using barycentric embeddings. Our approach allows the computation of several fiber directions in one coarse finite element, and thus, strongly decreases the required finite element resolution to predict muscle deformation during contraction. Using surface registration, fibers tracks of specific architecture can be transferred from a template to subject morphology, and then simulated. As a case study, three different architectures are simulated and compared to their equivalent one dimensional Hill wire model simulations.

  2. Real-time Adaptive Kinematic Model Estimation of Concentric Tube Robots.

    Science.gov (United States)

    Kim, Chunwoo; Ryu, Seok Chang; Dupont, Pierre E

    2015-01-01

    Kinematic models of concentric tube robots have matured from considering only tube bending to considering tube twisting as well as external loading. While these models have been demonstrated to approximate actual behavior, modeling error can be significant for medical applications that often call for positioning accuracy of 1-2mm. As an alternative to moving to more complex models, this paper proposes using sensing to adaptively update model parameters during robot operation. Advantages of this method are that the model is constantly tuning itself to provide high accuracy in the region of the workspace where it is currently operating. It also adapts automatically to changes in robot shape and compliance associated with the insertion and removal of tools through its lumen. As an initial exploration of this approach, a recursive on-line estimator is proposed and evaluated experimentally.

  3. 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.

  4. Real-time Closed-loop Control in a Rodent Model of Medically-induced Coma Using Burst Suppression

    Science.gov (United States)

    Ching, ShiNung; Liberman, Max Y.; Chemali, Jessica J.; Westover, M. Brandon; Kenny, Jonathan; Solt, Ken; Purdon, Patrick L.; Brown, Emery N.

    2013-01-01

    Background A medically-induced coma is an anesthetic state of profound brain inactivation created to treat status epilepticus and to provide cerebral protection following traumatic brain injuries. We hypothesized that a closed-loop anesthetic delivery system could automatically and precisely control the electroencephalogram state of burst suppression and efficiently maintain a medically-induced coma. Methods In six rats, we implemented a closed-loop anesthetic delivery system for propofol consisting of: a computer-controlled pump infusion, a two-compartment pharmacokinetics model defining propofol’s electroencephalogram effects, the burst suppression probability algorithm to compute in real time from the electroencephalogram the brain’s burst suppression state, an on-line parameter estimation procedure and a proportional-integral controller. In the control experiment each rat was randomly assigned to one of the six burst suppression probability target trajectories constructed by permuting the burst suppression probability levels of 0.4, 0.65 and 0.9 with linear transitions between levels. Results In each animal the controller maintained approximately 60 min of tight, real-time control of burst suppression by tracking each burst suppression probability target level for 15 min and two between-level transitions for 5 to 10 min. The posterior probability that the closed-loop anesthetic delivery system was reliable across all levels was 0.94 [95% confidence interval; (0.77 to 1.00) n = 18] and that the system was accurate was 1.00 [95% confidence interval; (0.84 to 1.00) n = 18]. Conclusion Our findings establish the feasibility of using a closed-loop anesthetic delivery systems to achieve in real-time reliable and accurate control of burst suppression in rodents and suggest a paradigm to precisely control medically-induced coma in patients. PMID:23770601

  5. 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

    preserves the original semantics of PACoR and enables the verification of PACoR systems using symbolic model checking in Uppaal and statistical model checking UppaalSMC. Finally we provide an example to illustrate system specification in PACoR, translation and verification....

  6. 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

  7. 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...

  8. 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.

  9. Model-Based Fault Diagnosis: Performing Root Cause and Impact Analyses in Real Time

    Science.gov (United States)

    Figueroa, Jorge F.; Walker, Mark G.; Kapadia, Ravi; Morris, Jonathan

    2012-01-01

    Generic, object-oriented fault models, built according to causal-directed graph theory, have been integrated into an overall software architecture dedicated to monitoring and predicting the health of mission- critical systems. Processing over the generic fault models is triggered by event detection logic that is defined according to the specific functional requirements of the system and its components. Once triggered, the fault models provide an automated way for performing both upstream root cause analysis (RCA), and for predicting downstream effects or impact analysis. The methodology has been applied to integrated system health management (ISHM) implementations at NASA SSC's Rocket Engine Test Stands (RETS).

  10. 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...

  11. 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.

  12. AERIS - applications for the environment : real-time information synthesis : eco-signal operations modeling report.

    Science.gov (United States)

    2014-12-01

    This report constitutes the detailed modeling and evaluation results of the Eco-Signal Operations Operational : Scenario defined by the AERIS program. The Operational Scenario constitutes four applications that are : designed to provide environmental...

  13. 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...

  14. 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.

  15. Real-time reservoir geological model updating using the hybrid EnKF and geostatistical technique

    Energy Technology Data Exchange (ETDEWEB)

    Li, H.; Chen, S.; Yang, D. [Regina Univ., SK (Canada). Petroleum Technology Research Centre

    2008-07-01

    Reservoir simulation plays an important role in modern reservoir management. Multiple geological models are needed in order to analyze the uncertainty of a given reservoir development scenario. Ideally, dynamic data should be incorporated into a reservoir geological model. This can be done by using history matching and tuning the model to match the past performance of reservoir history. This study proposed an assisted history matching technique to accelerate and improve the matching process. The Ensemble Kalman Filter (EnKF) technique, which is an efficient assisted history matching method, was integrated with a conditional geostatistical simulation technique to dynamically update reservoir geological models. The updated models were constrained to dynamic data, such as reservoir pressure and fluid saturations, and approaches geologically realistic at each time step by using the EnKF technique. The new technique was successfully applied in a heterogeneous synthetic reservoir. The uncertainty of the reservoir characterization was significantly reduced. More accurate forecasts were obtained from the updated models. 3 refs., 2 figs.

  16. How real-time cosmology can distinguish between different anisotropic models

    Science.gov (United States)

    Amendola, Luca; Eggers Bjæ lde, Ole; Valkenburg, Wessel; Wong, Yvonne Y. Y.

    2013-12-01

    We present a new analysis on how to distinguish between isotropic and anisotropic cosmological models based on tracking the angular displacements of a large number of distant quasars over an extended period of time, and then performing a multipole-vector decomposition of the resulting displacement maps. We find that while the GAIA mission operating at its nominal specifications does not have sufficient angular resolution to resolve anisotropic universes from isotropic ones using this method within a reasonable timespan of ten years, a next-generation GAIA-like survey with a resolution ten times better should be equal to the task. Distinguishing between different anisotropic models is however more demanding. Keeping the observational timespan to ten years, we find that the angular resolution of the survey will need to be of order 0.1 μas in order for certain rotating anisotropic models to produce a detectable signature that is also unique to models of this class. However, should such a detection become possible, it would immediately allow us to rule out large local void models.

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

    DEFF Research Database (Denmark)

    Sera, Dezso

    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...... and generic nature, and has the benefit of also being efficient in fast-changing conditions. Furthermore, the algorithm has been successfully implemented on a commercial PV inverter, currently on the market. In Chapter 3, an overview of the existing mathematical models used to describe the electrical...... behaviour of PV panels is given, followed by the parameter determination for the five-parameter single-exponential model based on datasheet values, which has been used for the implementation of a PV simulator taking in account the shape, size ant intensity of partial shadow in respect to bypass diodes...

  18. 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.

  19. Real-time mineral resource models : Approaches for the integration of online production data

    NARCIS (Netherlands)

    Benndorf, J.

    2014-01-01

    The flow of information along the mining value chain from exploration through resource modelling, reserve estimation, mine planning, operations management and beneficiation occurs typically in a discontinuous fashion over long time spans. Due to the uncertain nature of the knowledge about the

  20. 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...

  1. 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...

  2. Real-Time Model-Based Fault Detection of Continuous Glucose Sensor Measurements.

    Science.gov (United States)

    Turksoy, Kamuran; Roy, Anirban; Cinar, Ali

    2017-07-01

    Faults in subcutaneous glucose concentration readings with a continuous glucose monitoring (CGM) may affect the computation of insulin infusion rates that can lead to hypoglycemia or hyperglycemia in artificial pancreas control systems for patients with type 1 diabetes (T1D). Multivariable statistical monitoring methods are proposed for detection of faults in glucose concentration values reported by a subcutaneous glucose sensor. A nonlinear first principle glucose/insulin/meal dynamic model is developed. An unscented Kalman filter is used for state and parameter estimation of the nonlinear model. Principal component analysis models are developed and used for detection of dynamic changes. K-nearest neighbor classification algorithm is used for diagnosis of faults. Data from 51 subjects are used to assess the performance of the algorithm. The results indicate that the proposed algorithm works successfully with 84.2% sensitivity. Overall, 155 (out of 184) of the CGM failures are detected with a 2.8-min average detection time. A novel algorithm that integrates data-driven and model-based methods is developed. The proposed method is able to detect CGM failures with a high rate of success. The proposed fault detection algorithm can decrease the effects of faults on insulin infusion rates and reduce the potential for hypo- or hyperglycemia for patients with T1D.

  3. Stereo vision for planetary rovers - Stochastic modeling to near real-time implementation

    Science.gov (United States)

    Matthies, Larry

    1991-01-01

    JPL has achieved the first autonomous cross-country robotic traverses to use stereo vision, with all computing onboard the vehicle. This paper describes the stereo vision system, including the underlying statistical model and the details of the implementation. It is argued that the overall approach provides a unifying paradigm for practical domain-independent stereo ranging.

  4. Modelling and Analysis of Real Time Systems with Logic Programming and Constraints

    DEFF Research Database (Denmark)

    Banda, Gourinath

    Embedded systems are increasingly being deployed in a wide variety of applica- tions. Most, if not all, of these applications involve an electronic controller with discrete behaviour controlling a continuously evolving plant. Because of their hybrid behaviour (discrete and continuous) and reactive...... behaviour, the formal verification of embedded systems pose new challenges. Linear Hybrid Automata (LHA) is a language for specifying systems with linear hybrid behaviour. Abstract interpretation is a formal theory for approximating the semantics of programming languages. Model checking is a technique...... to verify the reactive behaviour of concur- rent systems. Computation Tree Logic (CTL) is a temporal property specification language. Logic programming is a general purpose programming language based on predicate logic. In this dissertation, the LHA models are verified by encoding them as con- straint logic...

  5. Modeling, Real-Time Estimation, and Identification of UWB Indoor Wireless Channels

    Directory of Open Access Journals (Sweden)

    Mohammed M. Olama

    2013-01-01

    Full Text Available Stochastic differential equations (SDEs are used to model ultrawideband (UWB indoor wireless channels. We show that the impulse responses for time-varying indoor wireless channels can be approximated in a mean-square sense as close as desired by impulse responses that can be realized by SDEs. The state variables represent the inphase and quadrature components of the UWB channel. The expected maximization and extended Kalman filter are employed to recursively identify and estimate the channel parameters and states, respectively, from online received signal strength measured data. Both resolvable and nonresolvable multipath received signals are considered and represented as small-scaled Nakagami fading. The proposed models together with the estimation algorithm are tested using UWB indoor measurement data demonstrating the method’s viability and the results are presented.

  6. [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.

  7. Modeling Passenger-Flow in Real-Time Bus Tracking System

    OpenAIRE

    Shalaik, Bashir; Jacob, Ricky; Winstanley, Adam C.

    2012-01-01

    Transit networks in the real world are similar to data transfer across a computer network. In this paper, we present the similarity and differences between computer networks and transit networks. We have developed a passenger-flow simulation model and we tested the effects of transit services provided on passengers in term of delay and passenger quality of service. We present the passenger’s behavior at bus stops, factors that affect passenger’s interactions with buses...

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

    Science.gov (United States)

    2015-06-01

    proportional controller proposed in [12] could be replaced by a two-part thrust actuation strategy such as ours, preserving the energy efficient hip ...rotate via an applied torque at the hip . The spring-mass system mimics animals that hop at a particular preferred frequency below which the motion requires...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

  9. Client Server Model Based DAQ System for Real-Time Air Pollution Monitoring

    OpenAIRE

    Vetrivel. P

    2014-01-01

    The proposed system consists of client server model based Data-Acquisition Unit. The Embedded Web Server integrates Pollution Server and DAQ that collects air Pollutants levels (CO, NO2, and SO2). The Pollution Server is designed by considering modern resource constrained embedded systems. In contrast, an application server is designed to the efficient execution of programs and scripts for supporting the construction of various applications. While a pollution server mainly dea...

  10. Musculoskeletal-see-through mirror: computational modeling and algorithm for whole-body muscle activity visualization in real time.

    Science.gov (United States)

    Murai, Akihiko; Kurosaki, Kosuke; Yamane, Katsu; Nakamura, Yoshihiko

    2010-12-01

    In this paper, we present a system that estimates and visualizes muscle tensions in real time using optical motion capture and electromyography (EMG). The system overlays rendered musculoskeletal human model on top of a live video image of the subject. The subject therefore has an impression that he/she sees the muscles with tension information through the cloth and skin. The main technical challenge lies in real-time estimation of muscle tension. Since existing algorithms using mathematical optimization to distribute joint torques to muscle tensions are too slow for our purpose, we develop a new algorithm that computes a reasonable approximation of muscle tensions based on the internal connections between muscles known as neuronal binding. The algorithm can estimate the tensions of 274 muscles in only 16 ms, and the whole visualization system runs at about 15 fps. The developed system is applied to assisting sport training, and the user case studies show its usefulness. Possible applications include interfaces for assisting rehabilitation. Copyright © 2010 Elsevier Ltd. All rights reserved.

  11. Real-time inverse kinematics for the upper limb: a model-based algorithm using segment orientations.

    Science.gov (United States)

    Borbély, Bence J; Szolgay, Péter

    2017-01-17

    Model based analysis of human upper limb movements has key importance in understanding the motor control processes of our nervous system. Various simulation software packages have been developed over the years to perform model based analysis. These packages provide computationally intensive-and therefore off-line-solutions to calculate the anatomical joint angles from motion captured raw measurement data (also referred as inverse kinematics). In addition, recent developments in inertial motion sensing technology show that it may replace large, immobile and expensive optical systems with small, mobile and cheaper solutions in cases when a laboratory-free measurement setup is needed. The objective of the presented work is to extend the workflow of measurement and analysis of human arm movements with an algorithm that allows accurate and real-time estimation of anatomical joint angles for a widely used OpenSim upper limb kinematic model when inertial sensors are used for movement recording. The internal structure of the selected upper limb model is analyzed and used as the underlying platform for the development of the proposed algorithm. Based on this structure, a prototype marker set is constructed that facilitates the reconstruction of model-based joint angles using orientation data directly available from inertial measurement systems. The mathematical formulation of the reconstruction algorithm is presented along with the validation of the algorithm on various platforms, including embedded environments. Execution performance tables of the proposed algorithm show significant improvement on all tested platforms. Compared to OpenSim's Inverse Kinematics tool 50-15,000x speedup is achieved while maintaining numerical accuracy. The proposed algorithm is capable of real-time reconstruction of standardized anatomical joint angles even in embedded environments, establishing a new way for complex applications to take advantage of accurate and fast model-based inverse

  12. 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.

  13. Real Time Energy Reconstruction in the ATLAS Hadronic Calorimeter and ATLAS sensitivity to Extra Dimension Models

    CERN Document Server

    Salvachua, Belen; Ros, Eduardo

    This work has been fulfilled within the ATLAS collaboration. I present here two studies, both related with the ATLAS detector and its operation. The ATLAS detector is described in chapter 1 whereas chapter 2 shows an introduction to the ATLAS tile calorimeter and the TileCal Read-Out Drivers (ROD) where the first part of the thesis is developed. In chapter 3 I present the study and the implementation of the Optimal Filtering algorithm in the TileCal Read-Out Drivers. The ROD provides the energy and the arrival time of the digital signal that is generated in the tile calorimeter. These parameters are reconstructed online using the Optimal Filtering algorithm, the RODs also provide a quality factor of the reconstruction. This information is sent to the standard ATLAS acquisition data flow with a specific data format defined in this thesis. Chapter 4 contains a short introduction to the Standard Model, presents its problems and describes other theories like Supersymmetry, Little Higgs or Extra Dimension models t...

  14. 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.

  15. 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

  16. 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.

  17. Green's functions from real-time bold-line Monte Carlo calculations: spectral properties of the nonequilibrium Anderson impurity model.

    Science.gov (United States)

    Cohen, Guy; Gull, Emanuel; Reichman, David R; Millis, Andrew J

    2014-04-11

    The nonequilibrium spectral properties of the Anderson impurity model with a chemical potential bias are investigated within a numerically exact real-time quantum Monte Carlo formalism. The two-time correlation function is computed in a form suitable for nonequilibrium dynamical mean field calculations. Additionally, the evolution of the model's spectral properties are simulated in an alternative representation, defined by a hypothetical but experimentally realizable weakly coupled auxiliary lead. The voltage splitting of the Kondo peak is confirmed and the dynamics of its formation after a coupling or gate quench are studied. This representation is shown to contain additional information about the dot's population dynamics. Further, we show that the voltage-dependent differential conductance gives a reasonable qualitative estimate of the equilibrium spectral function, but significant qualitative differences are found including incorrect trends and spurious temperature dependent effects.

  18. 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

  19. 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

  20. Real-Time Operation Of A Multipurpose Multi-Reservoir System Using A Distributed Hydrological Model And Quantitative Precipitation Forecast

    Science.gov (United States)

    Saavedra Valeriano, O. C.; Koike, T.; Yang, K.; Yang, D.

    2007-12-01

    Taking advantage of a distributed hydrological model's capabilities such as capturing spatial heterogeneity, this study couples a physically based hydrological model with embedded dam network operation to a heuristic model for real-time operation. The input rainfall is a meso-scale quantitative precipitation forecast at 0.125 degrees resolution issued every 6 hours. It was analyzed 3 different series and the complete 18 hours lead-time. The system attempts to 1) reduce flood peaks down stream and 2) replenish water level at reservoirs after flood event. The proposed scheme takes advantage of the heuristic algorithm in order to evaluate different release combination sets automatically based on stochastic seeding considering the dam constraints and objective function. Latter is defined to minimize the absolute difference between the forecasted flood volume at protecting point and the total released volume from reservoirs. To estimate the flood volume a desirable discharge is to be set at protecting point. The desirable discharge is defined as the average of observed values exceeding the mean annual discharge; however, this can be modified according to flood warning levels and water resources management. The optimization variables are the release-inflow ratios. In addition, it was introduced the standard deviation of the error forecast as a weight in the objective function. The developed system was applied to upper Tone River in Japan using up to three multipurpose reservoirs. The efficiency of the system's response was evident reducing the flood peaks and volume at protecting point comparing the optimized releases against observed data. This approach has shown feasibility to be used by dam operators as a real-time reference tool for more efficient water resources management.

  1. Tissue-specific selection of stable reference genes for real-time PCR normalization in an obese rat model.

    Science.gov (United States)

    Cabiati, Manuela; Raucci, Serena; Caselli, Chiara; Guzzardi, Maria Angela; D'Amico, Andrea; Prescimone, Tommaso; Giannessi, Daniela; Del Ry, Silvia

    2012-06-01

    Obesity is a complex pathology with interacting and confounding causes due to the environment, hormonal signaling patterns, and genetic predisposition. At present, the Zucker rat is an eligible genetic model for research on obesity and metabolic syndrome, allowing scrutiny of gene expression profiles. Real-time PCR is the benchmark method for measuring mRNA expressions, but the accuracy and reproducibility of its data greatly depend on appropriate normalization strategies. In the Zucker rat model, no specific reference genes have been identified in myocardium, kidney, and lung, the main organs involved in this syndrome. The aim of this study was to select among ten candidates (Actb, Gapdh, Polr2a, Ywhag, Rpl13a, Sdha, Ppia, Tbp, Hprt1 and Tfrc) a set of reference genes that can be used for the normalization of mRNA expression data obtained by real-time PCR in obese and lean Zucker rats both at fasting and during acute hyperglycemia. The most stable genes in the heart were Sdha, Tbp, and Hprt1; in kidney, Tbp, Actb, and Gapdh were chosen, while Actb, Ywhag, and Sdha were selected as the most stably expressed set for pulmonary tissue. The normalization strategy was used to analyze mRNA expression of tumor necrosis factor α, the main inflammatory mediator in obesity, whose variations were more significant when normalized with the appropriately selected reference genes. The findings obtained in this study underline the importance of having three stably expressed reference gene sets for use in the cardiac, renal, and pulmonary tissues of an experimental model of obese and hyperglycemic Zucker rats.

  2. A cognitive approach to game usability and design: mental model development in novice real-time strategy gamers.

    Science.gov (United States)

    Graham, John; Zheng, Liya; Gonzalez, Cleotilde

    2006-06-01

    We developed a technique to observe and characterize a novice real-time-strategy (RTS) player's mental model as it shifts with experience. We then tested this technique using an off-the-shelf RTS game, EA Games Generals. Norman defined mental models as, "an internal representation of a target system that provides predictive and explanatory power to the operator." In the case of RTS games, the operator is the player and the target system is expressed by the relationships within the game. We studied five novice participants in laboratory-controlled conditions playing a RTS game. They played Command and Conquer Generals for 2 h per day over the course of 5 days. A mental model analysis was generated using player dissimilarity-ratings of the game's artificial intelligence (AI) agents analyzed using multidimensional scaling (MDS) statistical methods. We hypothesized that novices would begin with an impoverished model based on the visible physical characteristics of the game system. As they gained experience and insight, their mental models would shift and accommodate the functional characteristics of the AI agents. We found that all five of the novice participants began with the predicted physical-based mental model. However, while their models did qualitatively shift with experience, they did not necessarily change to the predicted functional-based model. This research presents an opportunity for the design of games that are guided by shifts in a player's mental model as opposed to the typical progression through successive performance levels.

  3. Modeling real-time PCR kinetics: Richards reparametrized equation for quantitative estimation of European hake (Merluccius merluccius).

    Science.gov (United States)

    Sánchez, Ana; Vázquez, José A; Quinteiro, Javier; Sotelo, Carmen G

    2013-04-10

    Real-time PCR is the most sensitive method for detection and precise quantification of specific DNA sequences, but it is not usually applied as a quantitative method in seafood. In general, benchmark techniques, mainly cycle threshold (Ct), are the routine method for quantitative estimations, but they are not the most precise approaches for a standard assay. In the present work, amplification data from European hake (Merluccius merluccius) DNA samples were accurately modeled by three sigmoid reparametrized equations, where the lag phase parameter (λc) from the Richards equation with four parameters was demonstrated to be the perfect substitute for Ct for PCR quantification. The concentrations of primers and probes were subsequently optimized by means of that selected kinetic parameter. Finally, the linear correlation among DNA concentration and λc was also confirmed.

  4. 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

  5. eWaterCycle: real time assimilation of massive data streams into a hyper-resolution global hydrological model

    Science.gov (United States)

    Hut, Rolf; Sutanudjaja, Edwin; Drost, Niels; Steele-Dunne, Susan; de Jong, Kor; van Beek, Ludovicus; van de Giesen, Nick; Bierkens, Marc

    2013-04-01

    This research is focused on the ICT challenges involved in assimilating massive remote sensing datasets into a hyper-resolution hydrology model. The development of a hyper-resolution (100m) global hydrological model has recently been put forward as a "Grand Challenge" for the hydrological community. PCR-GLOBWB is a unique hydrological model including lateral flow and groundwater as well as human intervention through water consumption, dams and reservoir operations. Over the past decade, remotely sensed states, parameters and fluxes have become available through satellite observations. Exponential growth can be anticipated in the volume of hydrologically useful remote sensing data given the current plans of JAXA, NASA and ESA with respect to Earth observation satellites. Real time assimilation of these data into a hyper-resolution hydrology model would allow us to constrain the estimated states and fluxes and improve the model forecasts. However, this poses significant hydrological and ICT challenges. This project is a unique collaboration between hydrologists, and the computer scientists of the Netherlands eScience Center. Together, we will explore existing and novel ICT technologies to address the CPU and memory requirements of running the forward model. In addition, we will add data assimilation to this model, requiring streaming, management and processing of massive remote sensing datasets, as well as running the model for large ensembles and performing assimilation on a global scale.

  6. Real-time simulation of a spiking neural network model of the basal ganglia circuitry using general purpose computing on graphics processing units.

    Science.gov (United States)

    Igarashi, Jun; Shouno, Osamu; Fukai, Tomoki; Tsujino, Hiroshi

    2011-11-01

    Real-time simulation of a biologically realistic spiking neural network is necessary for evaluation of its capacity to interact with real environments. However, the real-time simulation of such a neural network is difficult due to its high computational costs that arise from two factors: (1) vast network size and (2) the complicated dynamics of biologically realistic neurons. In order to address these problems, mainly the latter, we chose to use general purpose computing on graphics processing units (GPGPUs) for simulation of such a neural network, taking advantage of the powerful computational capability of a graphics processing unit (GPU). As a target for real-time simulation, we used a model of the basal ganglia that has been developed according to electrophysiological and anatomical knowledge. The model consists of heterogeneous populations of 370 spiking model neurons, including computationally heavy conductance-based models, connected by 11,002 synapses. Simulation of the model has not yet been performed in real-time using a general computing server. By parallelization of the model on the NVIDIA Geforce GTX 280 GPU in data-parallel and task-parallel fashion, faster-than-real-time simulation was robustly realized with only one-third of the GPU's total computational resources. Furthermore, we used the GPU's full computational resources to perform faster-than-real-time simulation of three instances of the basal ganglia model; these instances consisted of 1100 neurons and 33,006 synapses and were synchronized at each calculation step. Finally, we developed software for simultaneous visualization of faster-than-real-time simulation output. These results suggest the potential power of GPGPU techniques in real-time simulation of realistic neural networks. Copyright © 2011 Elsevier Ltd. All rights reserved.

  7. Real-Time Logistics

    National Research Council Canada - National Science Library

    Agnes Shanley

    2017-01-01

    .... Working with T-Systems, a vendor of private cloud hosting, the companies are developing a proof of concept that would use blockchain-based smart contracts, with Roambee offering real-time product...

  8. 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).

  9. Model free approach to kinetic analysis of real-time hyperpolarized 13C magnetic resonance spectroscopy data.

    Directory of Open Access Journals (Sweden)

    Deborah K Hill

    Full Text Available Real-time detection of the rates of metabolic flux, or exchange rates of endogenous enzymatic reactions, is now feasible in biological systems using Dynamic Nuclear Polarization Magnetic Resonance. Derivation of reaction rate kinetics from this technique typically requires multi-compartmental modeling of dynamic data, and results are therefore model-dependent and prone to misinterpretation. We present a model-free formulism based on the ratio of total areas under the curve (AUC of the injected and product metabolite, for example pyruvate and lactate. A theoretical framework to support this novel analysis approach is described, and demonstrates that the AUC ratio is proportional to the forward rate constant k. We show that the model-free approach strongly correlates with k for whole cell in vitro experiments across a range of cancer cell lines, and detects response in cells treated with the pan-class I PI3K inhibitor GDC-0941 with comparable or greater sensitivity. The same result is seen in vivo with tumor xenograft-bearing mice, in control tumors and following drug treatment with dichloroacetate. An important finding is that the area under the curve is independent of both the input function and of any other metabolic pathways arising from the injected metabolite. This model-free approach provides a robust and clinically relevant alternative to kinetic model-based rate measurements in the clinical translation of hyperpolarized (13C metabolic imaging in humans, where measurement of the input function can be problematic.

  10. 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.

    2017-10-01

    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

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. Real-time modeling and online filtering of the stochastic error in a fiber optic current transducer

    Science.gov (United States)

    Wang, Lihui; Wei, Guangjin; Zhu, Yunan; Liu, Jian; Tian, Zhengqi

    2016-10-01

    The stochastic error characteristics of a fiber optic current transducer (FOCT) influence the relay protection, electric-energy metering, and other devices in the spacer layer. Real-time modeling and online filtering of the FOCT’s stochastic error tends to be an effective method for improving the measurement accuracy of the FOCT. This paper first pretreats and inspects the FOCT data, statistically. Then, the model order is set by the AIC principle to establish an ARMA (2,1) model and model’s applicability is tested. Finally, a Kalman filter is adopted to reduce the noise in the FOCT data. The results of the experiment and the simulation demonstrate that there is a notable decrease in the stochastic error after time series modeling and Kalman filtering. Besides, the mean-variance is decreased by two orders. All the stochastic error coefficients are decreased by the total variance method; the BI is decreased by 41.4%, the RRW is decreased by 67.5%, and the RR is decreased by 53.4%. Consequently, the method can reduce the stochastic error and improve the measurement accuracy of the FOCT, effectively.

  16. Development of a flash flood warning system based on real-time radar data and process-based erosion modelling

    Science.gov (United States)

    Schindewolf, Marcus; Kaiser, Andreas; Buchholtz, Arno; Schmidt, Jürgen

    2017-04-01

    Extreme rainfall events and resulting flash floods led to massive devastations in Germany during spring 2016. The study presented aims on the development of a early warning system, which allows the simulation and assessment of negative effects on infrastructure by radar-based heavy rainfall predictions, serving as input data for the process-based soil loss and deposition model EROSION 3D. Our approach enables a detailed identification of runoff and sediment fluxes in agricultural used landscapes. In a first step, documented historical events were analyzed concerning the accordance of measured radar rainfall and large scale erosion risk maps. A second step focused on a small scale erosion monitoring via UAV of source areas of heavy flooding events and a model reconstruction of the processes involved. In all examples damages were caused to local infrastructure. Both analyses are promising in order to detect runoff and sediment delivering areas even in a high temporal and spatial resolution. Results prove the important role of late-covering crops such as maize, sugar beet or potatoes in runoff generation. While e.g. winter wheat positively affects extensive runoff generation on undulating landscapes, massive soil loss and thus muddy flows are observed and depicted in model results. Future research aims on large scale model parameterization and application in real time, uncertainty estimation of precipitation forecast and interface developments.

  17. Estimation of low quantity genes: a hierarchical model for analyzing censored quantitative real-time PCR data.

    Science.gov (United States)

    Boyer, Tim C; Hanson, Tim; Singer, Randall S

    2013-01-01

    Analysis of gene quantities measured by quantitative real-time PCR (qPCR) can be complicated by observations that are below the limit of quantification (LOQ) of the assay. A hierarchical model estimated using MCMC methods was developed to analyze qPCR data of genes with observations that fall below the LOQ (censored observations). Simulated datasets with moderate to very high levels of censoring were used to assess the performance of the model; model results were compared to approaches that replace censored observations with a value on the log scale approximating zero or with values ranging from one to the LOQ of ten gene copies. The model was also compared to a Tobit regression model. Finally, all approaches for handling censored observations were evaluated with DNA extracted from samples that were spiked with known quantities of the antibiotic resistance gene tetL. For the simulated datasets, the model outperformed substitution of all values from 1-10 under all censoring scenarios in terms of bias, mean square error, and coverage of 95% confidence intervals for regression parameters. The model performed as well or better than substitution of a value approximating zero under two censoring scenarios (approximately 57% and 79% censored values). The model also performed as well or better than Tobit regression in two of three censoring scenarios (approximately 79% and 93% censored values). Under the levels of censoring present in the three scenarios of this study, substitution of any values greater than 0 produced the least accurate results. When applied to data produced from spiked samples, the model produced the lowest mean square error of the three approaches. This model provides a good alternative for analyzing large amounts of left-censored qPCR data when the goal is estimation of population parameters. The flexibility of this approach can accommodate complex study designs such as longitudinal studies.

  18. Estimation of low quantity genes: a hierarchical model for analyzing censored quantitative real-time PCR data.

    Directory of Open Access Journals (Sweden)

    Tim C Boyer

    Full Text Available Analysis of gene quantities measured by quantitative real-time PCR (qPCR can be complicated by observations that are below the limit of quantification (LOQ of the assay. A hierarchical model estimated using MCMC methods was developed to analyze qPCR data of genes with observations that fall below the LOQ (censored observations. Simulated datasets with moderate to very high levels of censoring were used to assess the performance of the model; model results were compared to approaches that replace censored observations with a value on the log scale approximating zero or with values ranging from one to the LOQ of ten gene copies. The model was also compared to a Tobit regression model. Finally, all approaches for handling censored observations were evaluated with DNA extracted from samples that were spiked with known quantities of the antibiotic resistance gene tetL. For the simulated datasets, the model outperformed substitution of all values from 1-10 under all censoring scenarios in terms of bias, mean square error, and coverage of 95% confidence intervals for regression parameters. The model performed as well or better than substitution of a value approximating zero under two censoring scenarios (approximately 57% and 79% censored values. The model also performed as well or better than Tobit regression in two of three censoring scenarios (approximately 79% and 93% censored values. Under the levels of censoring present in the three scenarios of this study, substitution of any values greater than 0 produced the least accurate results. When applied to data produced from spiked samples, the model produced the lowest mean square error of the three approaches. This model provides a good alternative for analyzing large amounts of left-censored qPCR data when the goal is estimation of population parameters. The flexibility of this approach can accommodate complex study designs such as longitudinal studies.

  19. Developing a public information and engagement portal of urban waterways with real-time monitoring and modeling.

    Science.gov (United States)

    Cochrane, T A; Wicke, D; O'Sullivan, A

    2011-01-01

    Waterways can contribute to the beauty and livelihood of urban areas, but maintaining their hydro-ecosystem health is challenging because they are often recipients of contaminated water from stormwater runoff and other discharges. Public awareness of local waterways' health and community impacts to these waterways is usually poor due to of lack of easily available information. To improve community awareness of water quality in urban waterways in New Zealand, a web portal was developed featuring a real-time waterways monitoring system, a public forum, historical data, interactive maps, contaminant modelling scenarios, mitigation recommendations, and a prototype contamination alert system. The monitoring system featured in the web portal is unique in the use of wireless mesh network technology, direct integration with online modelling, and a clear target of public engagement. The modelling aims to show the origin of contaminants within the local catchment and to help the community prioritize mitigation efforts to improve water quality in local waterways. The contamination alert system aims to keep managers and community members better informed and to provide a more timely response opportunity to avert any unplanned or accidental contamination of the waterways. Preliminary feedback has been positive and is being supported by local and regional authorities. The system was developed in a cost-effective manner providing a community focussed solution for quantifying and mitigating key contaminants in urban catchments and is applicable and transferable to other cities with similar stormwater challenges.

  20. Use of real-time QPCR in biokinetics and modeling of two different ammonia-oxidizing bacteria growing simultaneously.

    Science.gov (United States)

    Cho, Kyungjin; Nguyen, Duong Xuan; Lee, Seungyong; Hwang, Seokhwan

    2013-09-01

    A real-time quantitative polymerase chain reaction (QPCR) was used to evaluate biokinetic coefficients of Nitrosomonas nitrosa and N. cryotolerans clusters growing simultaneously in a batch mode of ammonia oxidation. The mathematical models based on Monod equation were employed to describe the competitive relationship between these clusters and were fitted to experimental data to obtain biokinetic values. The maximum growth rates (μ(m)), half-saturation coefficients (K(S)), microbial yields (Y) and decay coefficients (k(d)) of N. nitrosa and N. cryotolerans were 1.77 and 1.21 day(-1), 23.25 and 23.06 mg N·L(-1), 16 × 10(8) and 1 × 10(8) copies·mg N(-1), 0.26 and 0.20 day(-1), respectively. The estimated coefficients were applied for modeling continuous operations at various hydraulic retention times (HRTs) with an influent ammonia concentration of 300 mg N·L(-1). Modeling results revealed that ammonia oxidation efficiencies were achieved 55-98 % at 0.8-10 days HRTs and that the system was predicted to be washed out at HRT of 0.7 days. Overall, use of QPCR for estimating biokinetic coefficients of the two AOB cluster growing simultaneously by use of ammonia were successful. This idea may open a new direction towards biokinetics of ammonia oxidation in which respirometry tests are usually employed.

  1. 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.

  2. Establishment of a Real-Time, Quantitative, and Reproducible Mouse Model of Staphylococcus Osteomyelitis Using Bioluminescence Imaging

    Science.gov (United States)

    Funao, Haruki; Nagai, Shigenori; Sasaki, Aya; Hoshikawa, Tomoyuki; Aizawa, Mamoru; Okada, Yasunori; Chiba, Kazuhiro; Koyasu, Shigeo; Toyama, Yoshiaki; Matsumoto, Morio

    2012-01-01

    Osteomyelitis remains a serious problem in the orthopedic field. There are only a few animal models in which the quantity and distribution of bacteria can be reproducibly traced. Here, we established a real-time quantitative mouse model of osteomyelitis using bioluminescence imaging (BLI) without sacrificing the animals. A bioluminescent strain of Staphylococcus aureus was inoculated into the femurs of mice. The bacterial photon intensity (PI) was then sequentially measured by BLI. Serological and histological analyses of the mice were performed. The mean PI peaked at 3 days, and stable signals were maintained for over 3 months after inoculation. The serum levels of interleukin-6, interleukin-1β, and C-reactive protein were significantly higher in the infected mice than in the control mice on day 7. The serum monocyte chemotactic protein 1 level was also significantly higher in the infected group at 12 h than in the control group. A significantly higher proportion of granulocytes was detected in the peripheral blood of the infected group after day 7. Additionally, both acute and chronic histological manifestations were observed in the infected group. This model is useful for elucidating the pathophysiology of both acute and chronic osteomyelitis and to assess the effects of novel antibiotics or antibacterial implants. PMID:22104103

  3. 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.

  4. AROME-WMED, a real-time mesoscale model designed for the HyMeX special observation periods

    Science.gov (United States)

    Fourrié, N.; Bresson, É.; Nuret, M.; Jany, C.; Brousseau, P.; Doerenbecher, A.; Kreitz, M.; Nuissier, O.; Sevault, E.; Bénichou, H.; Amodei, M.; Pouponneau, F.

    2015-07-01

    During autumn 2012 and winter 2013, two special observation periods (SOPs) of the HYdrological cycle in the Mediterranean EXperiment (HyMeX) took place. For the preparatory studies and to support the instrument deployment during the field campaign, a dedicated version of the operational convective-scale Application of Research to Operations at Mesoscale (AROME)-France model was developed: the AROME-WMED (West Mediterranean Sea) model. It covers the western Mediterranean basin with a 48 h forecast range. It provided real-time analyses and forecasts which were sent daily to the HyMeX operational centre to forecast high-precipitation events and to help decision makers on the deployment of meteorological instruments. This paper presents the main features of this numerical weather prediction system in terms of data assimilation and forecast. Some specific data of the HyMeX SOP were assimilated in real time. The forecast skill of AROME-WMED is then assessed with objective scores and compared to the operational AROME-France model, for both autumn 2012 (05 September to 06 November 2012) and winter 2013 (01 February to 15 March 2013) SOPs. The overall performance of AROME-WMED is good for the first HyMeX special observation period (SOP1) (i.e. mean 2 m temperature root mean square error (RMSE) of 1.7 °C and mean 2 m relative humidity RMSE of 10 % for the 0-30 h forecast ranges) and similar to those of AROME-France for the 0-30 h common forecast range (maximal absolute difference of 2 m temperature RMSE of 0.2 °C and 0.21 % for the 2 m relative humidity); conversely, for the 24-48 h forecast range it is less accurate (relative loss between 10 and 12 % in 2 m temperature and relative humidity RMSE, and equitable threat score (ETS) for 24 h accumulated rainfall), but it remains useful for scheduling observation deployment. The characteristics of parameters, such as precipitation, temperature or humidity, are illustrated by one heavy precipitation case study that occurred

  5. 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

  6. 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

  7. 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 ...

  8. 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

  9. Comprehensive modeling study of ozonolysis of oleic acid aerosol based on real-time, online measurements of aerosol composition

    Science.gov (United States)

    Gallimore, P. J.; Griffiths, P. T.; Pope, F. D.; Reid, J. P.; Kalberer, M.

    2017-04-01

    The chemical composition of organic aerosols profoundly influences their atmospheric properties, but a detailed understanding of heterogeneous and in-particle reactivity is lacking. We present here a combined experimental and modeling study of the ozonolysis of oleic acid particles. An online mass spectrometry (MS) method, Extractive Electrospray Ionization (EESI), is used to follow the composition of the aerosol at a molecular level in real time; relative changes in the concentrations of both reactants and products are determined during aerosol aging. The results show evidence for multiple non-first-order reactions involving stabilized Criegee intermediates, including the formation of secondary ozonides and other oligomers. Offline liquid chromatography MS is used to confirm the online MS assignment of the monomeric and dimeric products. We explain the observed EESI-MS chemical composition changes, and chemical and physical data from previous studies, using a process-based aerosol chemistry simulation, the Pretty Good Aerosol Model (PG-AM). In particular, we extend previous studies of reactant loss by demonstrating success in reproducing the time dependence of product formation and the evolving particle size. This advance requires a comprehensive chemical scheme coupled to the partitioning of semivolatile products; relevant reaction and evaporation parameters have been refined using our new measurements in combination with PG-AM.

  10. 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

  11. 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.

  12. 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.

  13. Simultaneous real-time 3D photoacoustic tomography and EEG for neurovascular coupling study in an animal model of epilepsy

    Science.gov (United States)

    Wang, Bo; Xiao, Jiaying; Jiang, Huabei

    2014-08-01

    Objective. Neurovascular coupling in epilepsy is poorly understood; its study requires simultaneous monitoring of hemodynamic changes and neural activity in the brain. Approach. Here for the first time we present a combined real-time 3D photoacoustic tomography (PAT) and electrophysiology/electroencephalography (EEG) system for the study of neurovascular coupling in epilepsy, whose ability was demonstrated with a pentylenetetrazol (PTZ) induced generalized seizure model in rats. Two groups of experiments were carried out with different wavelengths to detect the changes of oxy-hemoglobin (HbO2) and deoxy-hemoglobin (HbR) signals in the rat brain. We extracted the average PAT signals of the superior sagittal sinus (SSS), and compared them with the EEG signal. Main results. Results showed that the seizure process can be divided into three stages. A ‘dip’ lasting for 1-2 min in the first stage and the following hyperfusion in the second stage were observed. The HbO2 signal and the HbR signal were generally negatively correlated. The change of blood flow was also estimated. All the acquired results here were in accordance with other published results. Significance. Compared to other existing functional neuroimaging tools, the method proposed here enables reliable tracking of hemodynamic signal with both high spatial and high temporal resolution in 3D, so it is more suitable for neurovascular coupling study of epilepsy.

  14. Real-time temperature estimation and monitoring of HIFU ablation through a combined modeling and passive acoustic mapping approach

    Science.gov (United States)

    Jensen, C. R.; Cleveland, R. O.; Coussios, C. C.

    2013-09-01

    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. Portions presented at the 13th International Symposium on Therapeutic Ultrasound, Heidelberg, Germany (2012).

  15. 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.

  16. Real-time measurement of kidney tubule fluid nitric oxide concentrations in early diabetes: disparate changes in different rodent models.

    Science.gov (United States)

    Levine, David Z; Iacovitti, Michelle

    2006-08-01

    There are several reports indicating that nitric oxide (NO) plays a role in the kidney hyperfiltration seen in the early stages of diabetes mellitus (DM). Whole kidney GFR and single nephron GFR (SNGFR) have been reported to decrease after nitric oxide synthase (NOS) inhibition. To date, no direct, in vivo, quantitative NO measurements have been made within the kidney in any models of early diabetes. To assess the possible association of changes in tubular fluid nitric oxide concentrations (TF [NO]) with early diabetes, a specially modified NO electrode with a tip diameter of about 7 microm was used to measure NO in single tubules in seven rodent groups. In the Sprague-Dawley (SD) rat model, TF [NO] increased by 50% after streptozotocin (STZ) induced DM1. In the B6129G2/J mouse, control TF [NO] was more than twice the rat control value and fell by 50% after STZ treatment. In three other groups of mice-db/db (B6.Cg-m+/+Lepr(db)/J) Type II diabetic (DM2) mouse, db/m (its heterozygote), and the corresponding wild type (WT)-TF [NO] was also much higher than in the rat, and unlike the B6129G2/J STZ diabetic mouse, did not change after the onset of diabetes. Blood glucose concentrations were similar in the three diabetic groups. Accordingly, in different rodent models of diabetes, in vivo TF [NO], measured in real time, varies significantly in control animals and directionally in different models of DM1 and DM2.

  17. Real-Time Evaluations

    Directory of Open Access Journals (Sweden)

    UNHCR

    2002-07-01

    Full Text Available A real-time evaluation (RTE is a timely, rapid andinteractive review of a fast evolving humanitarianoperation undertaken at an early phase. Its broadobjectives are to gauge the effectiveness and impactof a given UNHCR response and to ensure that itsfindings are used as an immediate catalyst fororganisational and operational change.

  18. Four-dimensional modelling of the mitral valve by real-time 3D transoesophageal echocardiography: proof of concept.

    Science.gov (United States)

    Noack, Thilo; Mukherjee, Chirojit; Kiefer, Philipp; Emrich, Fabian; Vollroth, Marcel; Ionasec, Razvan Ioan; Voigt, Ingmar; Houle, Helene; Ender, Joerg; Misfeld, Martin; Mohr, Friedrich Wilhelm; Seeburger, Joerg

    2015-02-01

    The complexity of the mitral valve (MV) anatomy and function is not yet fully understood. Assessing the dynamic movement and interaction of MV components to define MV physiology during the complete cardiac cycle remains a challenge. We herein describe a novel semi-automated 4D MV model. The model applies quantitative analysis of the MV over a complete cardiac cycle based on real-time 3D transoesophageal echocardiography (RT3DE) data. RT3DE data of MVs were acquired for 18 patients. The MV annulus and leaflets were semi-automatically reconstructed. Dimensions of the mitral annulus (anteroposterior and anterolateral-posteromedial diameter, annular circumference, annular area) and leaflets (MV orifice area, intercommissural distance) were acquired. Variability and reproducibility (intraclass correlation coefficient, ICC) for interobserver and intraobserver comparison were quantified at 4 time points during the cardiac cycle (mid-systole, end-systole, mid-diastole and end-diastole). Mitral annular dimensions provided highly reliable and reproducible measurements throughout the cardiac cycle for interobserver (variability range, 0.5-1.5%; ICC range, 0.895-0.987) and intraobserver (variability range, 0.5-1.6%; ICC range, 0.827-0.980) comparison, respectively. MV leaflet parameters showed a high reliability in the diastolic phase (variability range, 0.6-9.1%; ICC range, 0.750-0.986), whereas MV leaflet dimensions showed a high variability and lower correlation in the systolic phase (variability range, 0.6-22.4%; ICC range, 0.446-0.915) compared with the diastolic phase. This 4D model provides detailed morphological reconstruction as well as sophisticated quantification of the complex MV structure and dynamics throughout the cardiac cycle with a precision not yet described. © The Author 2014. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

  19. 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.

  20. Near Real-time GNSS-based Ionospheric Model using Expanded Kriging in the East Asia Region

    Science.gov (United States)

    Choi, P. H.; Bang, E.; Lee, J.

    2016-12-01

    Many applications which utilize radio waves (e.g. navigation, communications, and radio sciences) are influenced by the ionosphere. The technology to provide global ionospheric maps (GIM) which show ionospheric Total Electron Content (TEC) has been progressed by processing GNSS data. However, the GIMs have limited spatial resolution (e.g. 2.5° in latitude and 5° in longitude), because they are generated using globally-distributed and thus relatively sparse GNSS reference station networks. This study presents a near real-time and high spatial resolution TEC model over East Asia by using ionospheric observables from both International GNSS Service (IGS) and local GNSS networks and the expanded kriging method. New signals from multi-constellation (e.g,, GPS L5, Galileo E5) were also used to generate high-precision TEC estimates. The newly proposed estimation method is based on the universal kriging interpolation technique, but integrates TEC data from previous epochs to those from the current epoch to improve the TEC estimation performance by increasing ionospheric observability. To propagate previous measurements to the current epoch, we implemented a Kalman filter whose dynamic model was derived by using the first-order Gauss-Markov process which characterizes temporal ionospheric changes under the nominal ionospheric conditions. Along with the TEC estimates at grids, the method generates the confidence bounds on the estimates using resulting estimation covariance. We also suggest to classify the confidence bounds into several categories to allow users to recognize the quality levels of TEC estimates according to the requirements for user's applications. This paper examines the performance of the proposed method by obtaining estimation results for both nominal and disturbed ionospheric conditions, and compares these results to those provided by GIM of the NASA Jet propulsion Laboratory. In addition, the estimation results based on the expanded kriging method are

  1. Near real time modeling of the local ionospheric VTEC with particle filter using ground base GPS observations

    Science.gov (United States)

    Onur Karslıoǧlu, Mahmut; Aghakarimi, Armin

    2013-04-01

    Ionosphere modeling is an important field of current studies because of its influences on the propagation of the electromagnetic signals. Among the various methods of obtaining ionospheric information, Global Positioning System (GPS) is the most prominent one because of extensive stations which are distributed all over the world. There are several studies in the literature related to the modeling of the ionosphere in terms of Total Electron Content (TEC). However, most of these studies investigate the ionosphere in the global and regional scales. On the other hand, complex dynamic of the ionosphere requires further studies in the local structure of the TEC distribution. In this work, Particle filter has been used for the investigation of the local character of the ionospheric Vertical Total Electron Content (VTEC). The GPS data of 29 ground based GPS stations, belonging to International GNSS Service (IGS) and Reference Frame Sub-commission for Europe (EUREF), for Europe have been used in this study. The data acquisition time is 18 February 2011 and the data is affected by the 15 February geomagnetic storm. In the preprocessing step, the observations of each satellite are examined for any possible cycle slip and also geometry-free linear combination of the observables are calculated for each continuous arc. Then, Pseudorange observations smoothed with the carrier to code leveling method. Particle filter is used for near-real time estimation of the VTEC and of the combined satellite and receiver biases. The Particle filter is implemented by recursively generating a set of weighted samples of the state variables. This filter has a flexible nature which can be more adaptive to some characteristics of the high dynamic systems. Besides, standard Kalman filter as an effective method for optimal state estimation is applied to the same data sets to compare the corresponding results with results of Particle filter. The comparison shows that Particle filter indicates better

  2. 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...

  3. 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.

  4. 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%.

  5. Evaluation of Early Kidney Damage Caused by Brain Death Using Real-Time Ultrasound Elastography in a Bama Pig Model.

    Science.gov (United States)

    Tang, Ying; Zhao, Jingwen; Liu, Dongyang; Niu, Ningning; Yu, Huimin

    2017-10-01

    The aim of this study was to investigate the value of real-time tissue elastography (RTE) in the evaluation of early graft damage resulting from brain death. We performed RTE before and 0, 3, 6 and 9 h after brain death in a Bama pig model. Eleven RTE parameters were compared among time groups, and their correlations with electron microscopic findings were analyzed. Receiver operating characteristic curve analysis was used to find the RTE parameter cutoff values. The mean relative strain value within the region of interest (MEAN), standard deviation of the relative strain value within the region of interest (SD), percentage area of low strain within the region of interest (%AREA), complexity of low-strain area within the region of interest (COMP), kurtosis (KURT), skewness (SKEW), contrast (CONT) and entropy (ENT) and inverse difference moment (IDM) differed statistically significantly between groups (p < 0.05). Electron microscopy of kidney tissue revealed that irreversible damage gradually occurred with longer brain death duration and was marked at 9 h (p < 0.05). These findings correlated best with MEAN (r = 0.632, p < 0.05). Receiver operating characteristic curve analysis of RTE parameters identified a cutoff value of 63.43 for MEAN for optimal diagnostic performance. RTE allows non-invasive, preliminary evaluation of early renal graft damage resulting from brain death. Copyright © 2017 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

  6. 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.

  7. 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

  8. 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

  9. Real-time in vivo green fluorescent protein imaging of a murine leishmaniasis model as a new tool for Leishmania vaccine and drug discovery.

    Science.gov (United States)

    Mehta, Sanjay R; Huang, Robert; Yang, Meng; Zhang, Xing-Quan; Kolli, Bala; Chang, Kwang-Poo; Hoffman, Robert M; Goto, Yasuyuki; Badaro, Roberto; Schooley, Robert T

    2008-12-01

    Leishmania species are obligate intracellular protozoan parasites that cause a broad spectrum of clinical diseases in mammalian hosts. The most frequently used approach to quantify parasites in murine model systems is based on thickness measurements of the footpad or ear after experimental infection. To overcome the limitations of this method, we used a Leishmania mutant episomally transfected with enhanced green fluorescent protein, enabling in vivo real-time whole-body fluorescence imaging, to follow the progression of Leishmania infection in parasitized tissues. Fluorescence correlated with the number of Leishmania parasites in the tissue and demonstrated the real-time efficacy of a therapeutic vaccine. This approach provides several substantial advantages over currently available animal model systems for the in vivo study of immunopathogenesis, prevention, and therapy of leishmaniasis. These include improvements in sensitivity and the ability to acquire real-time data on progression and spread of the infection.

  10. 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

  11. Reference genes for real-time PCR quantification of microRNAs and messenger RNAs in rat models of hepatotoxicity.

    Directory of Open Access Journals (Sweden)

    María N Lardizábal

    Full Text Available Hepatotoxicity is associated with major changes in liver gene expression induced by xenobiotic exposure. Understanding the underlying mechanisms is critical for its clinical diagnosis and treatment. MicroRNAs are key regulators of gene expression that control mRNA stability and translation, during normal development and pathology. The canonical technique to measure gene transcript levels is Real-Time qPCR, which has been successfully modified to determine the levels of microRNAs as well. However, in order to obtain accurate data in a multi-step method like RT-qPCR, the normalization with endogenous, stably expressed reference genes is mandatory. Since the expression stability of candidate reference genes varies greatly depending on experimental factors, the aim of our study was to identify a combination of genes for optimal normalization of microRNA and mRNA qPCR expression data in experimental models of acute hepatotoxicity. Rats were treated with four traditional hepatotoxins: acetaminophen, carbon tetrachloride, D-galactosamine and thioacetamide, and the liver expression levels of two groups of candidate reference genes, one for microRNA and the other for mRNA normalization, were determined by RT-qPCR in compliance with the MIQE guidelines. In the present study, we report that traditional reference genes such as U6 spliceosomal RNA, Beta Actin and Glyceraldehyde-3P-dehydrogenase altered their expression in response to classic hepatotoxins and therefore cannot be used as reference genes in hepatotoxicity studies. Stability rankings of candidate reference genes, considering only those that did not alter their expression, were determined using geNorm, NormFinder and BestKeeper software packages. The potential candidates whose measurements were stable were further tested in different combinations to find the optimal set of reference genes that accurately determine mRNA and miRNA levels. Finally, the combination of MicroRNA-16/5S Ribosomal RNA and

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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...

  18. Development of tools for evaluating rainfall estimation models in real- time using the Integrated Meteorological Observation Network in Castilla y León (Spain)

    Science.gov (United States)

    Merino, Andres; Guerrero-Higueras, Angel Manuel; López, Laura; Gascón, Estibaliz; Sánchez, José Luis; Lorente, José Manuel; Marcos, José Luis; Matía, Pedro; Ortiz de Galisteo, José Pablo; Nafría, David; Fernández-González, Sergio; Weigand, Roberto; Hermida, Lucía; García-Ortega, Eduardo

    2014-05-01

    The integration of various public and private observation networks into the Observation Network of Castile-León (ONet_CyL), Spain, allows us to monitor the risks in real-time. One of the most frequent risks in this region is severe precipitation. Thus, the data from the network allows us to determine the area where precipitation was registered and also to know the areas with precipitation in real-time. The observation network is managed with a LINUX system. The observation platform makes it possible to consult the observation data in a specific point in the region, or otherwise to see the spatial distribution of the precipitation in a user-defined area and time interval. In this study, we compared several rainfall estimation models, based on satellite data for Castile-León, with precipitation data from the meteorological observation network. The rainfall estimation models obtained from the meteorological satellite data provide us with a precipitation field covering a wide area, although its operational use requires a prior evaluation using ground truth data. The aim is to develop a real-time evaluation tool for rainfall estimation models that allows us to monitor the accuracy of its forecasting. This tool makes it possible to visualise different Skill Scores (Probability of Detection, False Alarm Ratio and others) of each rainfall estimation model in real time, thereby not only allowing us to know the areas where the rainfall models indicate precipitation, but also the validation of the model in real-time for each specific meteorological situation. Acknowledgements The authors would like to thank the Regional Government of Castile-León for its financial support through the project LE220A11-2. This study was supported by the following grants: GRANIMETRO (CGL2010-15930); MICROMETEO (IPT-310000-2010-22).

  19. Imaging visceral leishmaniasis in real time with golden hamster model: Monitoring the parasite burden and hamster transcripts to further characterize the immunological responses of the host.

    Science.gov (United States)

    Rouault, Eline; Lecoeur, Hervé; Meriem, Asma Ben; Minoprio, Paola; Goyard, Sophie; Lang, Thierry

    2017-02-01

    Characterizing the clinical, immunological and parasitological features associated with visceral leishmaniasis is complex. It involves recording in real time and integrating quantitative multi-parametric data sets from parasite infected host tissues. Although several models have been used, hamsters are considered the bona fide experimental model for Leishmania donovani studies. To study visceral leishmaniasis in hamsters we generated virulent transgenic L. donovani that stably express a reporter luciferase protein. Two complementary methodologies were combined to follow the infectious process: in vivo imaging using luciferase-expressing Leishmania and real time RT-PCR to quantify both Leishmania and host transcripts. This approach allows us: i) to assess the clinical outcome of visceral leishmaniasis by individual monitoring of hamster weight, ii) to follow the parasite load in several organs by real time analysis of the bioluminescence in vivo and through real time quantitative PCR analysis of amastigote parasite transcript abundance ex vivo, iii) to evaluate the immunological responses triggered by the infection by quantifying hamster transcripts on the same samples and iv) to limit the number of hamsters selected for further analysis. The overall data highlight a correlation between the transcriptional cytokine signatures of hamster affected tissues and the amastigote burden fluctuations, thus providing new insights into the immunopathological process driven by L. donovani in the tissues of mammalian hosts. Finally, they suggest organ-specific immune responses. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  20. 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.

  1. A Real-Time Eulerian Photochemical Model Forecast System: Overview and Initial Ozone Forecast Performance in the Northeast U.S. Corridor.

    Science.gov (United States)

    McHenry, John N.; Ryan, William F.; Seaman, Nelson L.; Coats, Carlie J., Jr.; Pudykiewicz, Janusz; Arunachalam, Sarav; Vukovich, Jeffery M.

    2004-04-01

    This article reports on the first implementation of a real-time Eulerian photochemical model forecast system in the United States. The forecast system consists of a tripartite set of one-way coupled models that run routinely on a parallel microprocessor supercomputer. The component models are the fifth-generation Pennsylvania State University (PSU) NCAR Mesoscale Model (MM5), the Sparse-Matrix Operator Kernel for Emissions (SMOKE) model, and the Multiscale Air Quality Simulation Platform—Real Time (MAQSIP-RT) photochemical model. Though the system has been run in real time since the summer of 1998, forecast results obtained during August of 2001 at 15-km grid spacing over New England and the northern mid-Atlantic—conducted as part of an “early start” NOAA air quality forecasting initiative—are described in this article.The development and deployment of a real-time numerical air quality prediction (NAQP) system is technically challenging. MAQSIP-RT contains a full pho-tochemical oxidant gas-phase chemical mechanism together with transport, dry deposition, and sophisticated cloud treatment. To enable the NAQP system to run fast enough to meet operational forecast deadlines, significant work was devoted to data flow design and software engineering of the models and control codes. The result is a turnkey system now in use by a number of agencies concerned with operational ozone forecasting.Results of the chosen episode are compared against three other models/modeling techniques: a traditional statistical model used routinely in the metropolitan Philadelphia, Pennsylvania, area, a set of publicly issued forecasts in the northeastern United States, and the operational Canadian Hemispheric and Regional Ozone and NOx System (CHRONOS) model. For the test period it is shown that the NAQP system performs as well or better than all of these operational approaches. Implications for the impending development of an operational U.S. ozone forecasting capability are

  2. Real-Time Monitoring of Nuclear Factor κB Activity in Cultured Cells and in Animal Models

    Directory of Open Access Journals (Sweden)

    Christian E. Badr

    2009-09-01

    Full Text Available Nuclear factor κB (NF-κB is a transcription factor that plays a major role in many human disorders, including immune diseases and cancer. We designed a reporter system based on NF-κB responsive promoter elements driving expression of the secreted Gaussia princeps luciferase (Gluc. We show that this bioluminescent reporter is a highly sensitive tool for noninvasive monitoring of the kinetics of NF-κB activation and inhibition over time, both in conditioned medium of cultured cells and in the blood and urine of animals. NF-κB activation was successfully monitored in real time in endothelial cells in response to tumor angiogenic signaling, as well as in monocytes in response to inflammation. Further, we demonstrated dual blood monitoring of both NF-κB activation during tumor development as correlated to tumor formation using the NF-κB Gluc reporter, as well as the secreted alkaline phosphatase reporter. This NF-κB reporter system provides a powerful tool for monitoring NF-κB activity in real time in vitro and in vivo.

  3. SETI meets a social intelligence: Dolphins as a model for real-time interaction and communication with a sentient species

    Science.gov (United States)

    Herzing, Denise L.

    2010-12-01

    In the past SETI has focused on the reception and deciphering of radio signals from potential remote civilizations. It is conceivable that real-time contact and interaction with a social intelligence may occur in the future. A serious look at the development of relationship, and deciphering of communication signals within and between a non-terrestrial, non-primate sentient species is relevant. Since 1985 a resident community of free-ranging Atlantic spotted dolphins has been observed regularly in the Bahamas. Life history, relationships, regular interspecific interactions with bottlenose dolphins, and multi-modal underwater communication signals have been documented. Dolphins display social communication signals modified for water, their body types, and sensory systems. Like anthropologists, human researchers engage in benign observation in the water and interact with these dolphins to develop rapport and trust. Many individual dolphins have been known for over 20 years. Learning the culturally appropriate etiquette has been important in the relationship with this alien society. To engage humans in interaction the dolphins often initiate spontaneous displays, mimicry, imitation, and synchrony. These elements may be emergent/universal features of one intelligent species contacting another for the intention of initiating interaction. This should be a consideration for real-time contact and interaction for future SETI work.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. Investigation of hit-and-run crash occurrence and severity using real-time loop detector data and hierarchical Bayesian binary logit model with random effects.

    Science.gov (United States)

    Xie, Meiquan; Cheng, Wen; Gill, Gurdiljot Singh; Zhou, Jiao; Jia, Xudong; Choi, Simon

    2017-08-24

    Most of the extensive research dedicated to identifying the influential factors of hit-and-run (HR) crashes has utilized typical maximum likelihood estimation binary logit models, and none have employed real-time traffic data. To fill this gap, this study focused on investigating factors contributing to HR crashes, as well as the severity levels of HR. This study analyzed 4-year crash and real-time loop detector data by employing hierarchical Bayesian models with random effects within a sequential logit structure. In addition to evaluation of the impact of random effects on model fitness and complexity, the prediction capability of the models was examined. Stepwise incremental sensitivity and specificity were calculated and receiver operating characteristic (ROC) curves were utilized to graphically illustrate the predictive performance of the model. Among the real-time flow variables, the average occupancy and speed from the upstream detector were observed to be positively correlated with HR crash possibility. The average upstream speed and speed difference between upstream and downstream speeds were correlated with the occurrence of severe HR crashes. In addition to real-time factors, other variables found influential for HR and severe HR crashes were length of segment, adverse weather conditions, dark lighting conditions with malfunctioning street lights, driving under the influence of alcohol, width of inner shoulder, and nighttime. This study suggests the potential traffic conditions of HR and severe HR occurrence, which refer to relatively congested upstream traffic conditions with high upstream speed and significant speed deviations on long segments. The above findings suggest that traffic enforcement should be directed toward mitigating risky driving under the aforementioned traffic conditions. Moreover, enforcement agencies may employ alcohol checkpoints to counter driving under the influence (DUI) at night. With regard to engineering improvements, wider

  11. Real-time flood forecasting

    Science.gov (United States)

    Lai, C.; Tsay, T.-K.; Chien, C.-H.; Wu, I.-L.

    2009-01-01

    Researchers at the Hydroinformatic Research and Development Team (HIRDT) of the National Taiwan University undertook a project to create a real time flood forecasting model, with an aim to predict the current in the Tamsui River Basin. The model was designed based on deterministic approach with mathematic modeling of complex phenomenon, and specific parameter values operated to produce a discrete result. The project also devised a rainfall-stage model that relates the rate of rainfall upland directly to the change of the state of river, and is further related to another typhoon-rainfall model. The geographic information system (GIS) data, based on precise contour model of the terrain, estimate the regions that were perilous to flooding. The HIRDT, in response to the project's progress, also devoted their application of a deterministic model to unsteady flow of thermodynamics to help predict river authorities issue timely warnings and take other emergency measures.

  12. Real-time flutter analysis

    Science.gov (United States)

    Walker, R.; Gupta, N.

    1984-01-01

    The important algorithm issues necessary to achieve a real time flutter monitoring system; namely, the guidelines for choosing appropriate model forms, reduction of the parameter convergence transient, handling multiple modes, the effect of over parameterization, and estimate accuracy predictions, both online and for experiment design are addressed. An approach for efficiently computing continuous-time flutter parameter Cramer-Rao estimate error bounds were developed. This enables a convincing comparison of theoretical and simulation results, as well as offline studies in preparation for a flight test. Theoretical predictions, simulation and flight test results from the NASA Drones for Aerodynamic and Structural Test (DAST) Program are compared.

  13. Demonstration of a Very Inexpensive, Turbidimetric, Real-Time, RT-LAMP Detection Platform Using Shrimp Laem-Singh Virus (LSNV) as a Model

    OpenAIRE

    Narong Arunrut; Rungkarn Suebsing; Boonsirm Withyachumnarnkul; Wansika Kiatpathomchai

    2014-01-01

    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 a...

  14. 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.

  15. Integrating real-time and manual monitored data to predict hillslope soil moisture dynamics with high spatio-temporal resolution using linear and non-linear models

    Science.gov (United States)

    Zhu, Qing; Zhou, Zhiwen; Duncan, Emily W.; Lv, Ligang; Liao, Kaihua; Feng, Huihui

    2017-02-01

    Spatio-temporal variability of soil moisture (θ) is a challenge that remains to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time θ monitoring methods. This restricted the comprehensive and intensive examination of θ dynamics. In this study, we integrated the manual and real-time monitored data to depict the hillslope θ dynamics with good spatial coverage and temporal resolution. Linear (stepwise multiple linear regression-SMLR) and non-linear (support vector machines-SVM) models were used to predict θ at 39 manual sites (collected 1-2 times per month) with θ collected at three real-time monitoring sites (collected every 5 mins). By comparing the accuracies of SMLR and SVM for each depth and manual site, an optimal prediction model was then determined at this depth of this site. Results showed that θ at the 39 manual sites can be reliably predicted (root mean square errors index, profile curvature, and θ temporal stability influenced the selection of prediction model since they were related to the subsurface soil water distribution and movement. Using this approach, hillslope θ spatial distributions at un-sampled times and dates can be predicted. Missing information of hillslope θ dynamics can be acquired successfully.

  16. 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.

  17. 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.

  18. Computer optimization techniques for NASA Langley's CSI evolutionary model's real-time control system. [Controls/Structure Interaction

    Science.gov (United States)

    Elliott, Kenny B.; Ugoletti, Roberto; Sulla, Jeff

    1992-01-01

    The evolution and optimization of a real-time digital control system is presented. The control system is part of a testbed used to perform focused technology research on the interactions of spacecraft platform and instrument controllers with the flexible-body dynamics of the platform and platform appendages. The control system consists of Computer Automated Measurement and Control (CAMAC) standard data acquisition equipment interfaced to a workstation computer. The goal of this work is to optimize the control system's performance to support controls research using controllers with up to 50 states and frame rates above 200 Hz. The original system could support a 16-state controller operating at a rate of 150 Hz. By using simple yet effective software improvements, Input/Output (I/O) latencies and contention problems are reduced or eliminated in the control system. The final configuration can support a 16-state controller operating at 475 Hz. Effectively the control system's performance was increased by a factor of 3.

  19. Real-time holographic deconvolution techniques for one-way image transmission through an aberrating medium: characterization, modeling, and measurements

    Science.gov (United States)

    Haji-Saeed, B.; Sengupta, S. K.; Testorf, M.; Goodhue, W.; Khoury, J.; Woods, C. L.; Kierstead, J.

    2006-05-01

    We propose and demonstrate a new photorefractive real-time holographic deconvolution technique for adaptive one-way image transmission through aberrating media by means of four-wave mixing. In contrast with earlier methods, which typically required various codings of the exact phase or two-way image transmission for correcting phase distortion, our technique relies on one-way image transmission through the use of exact phase information. Our technique can simultaneously correct both amplitude and phase distortions. We include several forms of image degradation, various test cases, and experimental results. We characterize the performance as a function of the input beam ratios for four metrics: signal-to-noise ratio, normalized root-mean-square error, edge restoration, and peak-to-total energy ratio. In our characterization we use false-color graphic images to display the best beam-intensity ratio two-dimensional region(s) for each of these metrics. Test cases are simulated at the optimal values of the beam-intensity ratios. We demonstrate our results through both experiment and computer simulation.

  20. Real-time decay of a highly excited charge carrier in the one-dimensional Holstein model

    Science.gov (United States)

    Dorfner, F.; Vidmar, L.; Brockt, C.; Jeckelmann, E.; Heidrich-Meisner, F.

    2015-03-01

    We study the real-time dynamics of a highly excited charge carrier coupled to quantum phonons via a Holstein-type electron-phonon coupling. This is a prototypical example for the nonequilibrium dynamics in an interacting many-body system where excess energy is transferred from electronic to phononic degrees of freedom. We use diagonalization in a limited functional space (LFS) to study the nonequilibrium dynamics on a finite one-dimensional chain. This method agrees with exact diagonalization and the time-evolving block-decimation method, in both the relaxation regime and the long-time stationary state, and among these three methods it is the most efficient and versatile one for this problem. We perform a comprehensive analysis of the time evolution by calculating the electron, phonon and electron-phonon coupling energies, and the electronic momentum distribution function. The numerical results are compared to analytical solutions for short times, for a small hopping amplitude and for a weak electron-phonon coupling. In the latter case, the relaxation dynamics obtained from the Boltzmann equation agrees very well with the LFS data. We also study the time dependence of the eigenstates of the single-site reduced density matrix, which defines the so-called optimal phonon modes. We discuss their structure in nonequilibrium and the distribution of their weights. Our analysis shows that the structure of optimal phonon modes contains very useful information for the interpretation of the numerical data.

  1. 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.

  2. 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.

  3. Deciphering PDT-induced inflammatory responses using real-time FDG-PET in a mouse tumour model.

    Science.gov (United States)

    Cauchon, Nicole; Hasséssian, Haroutioun M; Turcotte, Eric; Lecomte, Roger; van Lier, Johan E

    2014-10-01

    Dynamic positron emission tomography (PET), combined with constant infusion of 2-deoxy-2-[(18)F]fluoro-d-glucose (FDG), enables real-time monitoring of transient metabolic changes in vivo, which can serve to understand the underlying physiology. Here we investigated characteristic changes in the tumour FDG-uptake profiles in relation to acute localized inflammatory responses induced by photodynamic therapy (PDT). Dynamic PET imaging with constant FDG infusion was used with EMT-6 tumour bearing mice. FDG time-activity uptake curves were measured simultaneously, in treated and reference tumours, for 3 hours, before, during and after PDT light treatment. Inflammation was studied when evoked, either by PDT using a trisulfonated porphyrazine photosensitizer, or lipopolysaccharide (LPS), and inhibited using indomethacin. The distinct transient patterns, characterized by drops and subsequent recovery of tumour FDG uptake rates, were also analysed using immunohistochemical markers for apoptosis, necrosis, and inflammation. Typical profiles for tumour FDG-uptake, consisted of a drop during PDT, followed by a gradual recovery period. Tumours treated with LPS, but not with light, showed a continuous increase in FDG-uptake during the 3 h experimental period. Treatment with indomethacin, inhibited the rise in FDG-uptake observed with either LPS or PDT. Tumour FDG-uptake profiles correlated with necrosis markers during PDT, and inflammatory response markers post-PDT, but not with an apoptosis marker at any time during or after PDT. Dynamic FDG-PET imaging combined with indomethacin reveals that, the drop in the tumour FDG-uptake rate during the PDT illumination phase reflects vascular collapse and necrosis, while the increased tumour FDG-uptake rate immediately post-illumination involves an acute localized inflammatory response. Dynamic FDG infusion and PET imaging, combined with the use of selective inhibitors, provides unique insight for deciphering the complex underlying

  4. Particle filter-based real-time estimation and prediction of traffic conditions. In: Christos H. Skiadas (Ed.), Recent Advances in Stochastic Modelling and Data Analysis

    OpenAIRE

    Sau, J.; EL-FAOUZI, NE; BEN-AISSA, A; DE MOUZON, O

    2007-01-01

    Real-time estimation and short-term prediction of traffic conditions is one of major concern of traffic managers and ITS-oriented systems. Model-based methods appear now as very promising ways in order to reach this purpose. Such methods are already used in process control (Kalman filtering, Luenberger observers). In the application presented in this paper, due to the high non linearity of the traffic models, particle filter (PF) approach is applied in combination with the well-known first or...

  5. Towards Real-Time Argumentation

    OpenAIRE

    Vicente JULIÁN; Martí NAVARRO; Botti, Vicente; Stella HERAS

    2015-01-01

    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 a...

  6. 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.

  7. Designing Real Time Assistive Technologies

    DEFF Research Database (Denmark)

    Sonne, Tobias; Obel, Carsten; Grønbæk, Kaj

    2015-01-01

    design criteria in relation to three core components (sensing, recognizing, and assisting) for designing real time assistive technologies for children with ADHD. Based on these design criteria, we designed the Child Activity Sensing and Training Tool (CASTT), a real time assistive prototype that captures...... activities and assists the child in maintaining attention. From a preliminary evaluation of CASTT with 20 children in several schools, we and found that: 1) it is possible to create a wearable sensor system for children with ADHD that monitors physical and physiological activities in real time; and that 2......) real time assistive technologies have potential to assist children with ADHD in regaining attention in critical school situations....

  8. 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.

  9. Real-time Service Acounting

    NARCIS (Netherlands)

    Le, V.M.; van Beijnum, Bernhard J.F.; de Goede, Leo; Cheng, T.

    2002-01-01

    Offering telematics services toward the end-users involves inter-domain real-time service provisioning, it therefore can also involves inter-domain real-time service accounting. Recognizing the increasing complexity of accounting services due to dynamic service usage behavior of the end-users, the

  10. Real-time volume graphics

    CERN Document Server

    Engel, Klaus; Kniss, Joe; Rezk-Salama, Christof; Weiskopf, Daniel

    2006-01-01

    Based on course notes of SIGGRAPH course teaching techniques for real-time rendering of volumetric data and effects; covers both applications in scientific visualization and real-time rendering. Starts with the basics (texture-based ray casting) and then improves and expands the algorithms incrementally. Book includes source code, algorithms, diagrams, and rendered graphics.

  11. Feasibility of real-time intestinal bloodstream evaluation using probe-based confocal laser endomicroscopy in a porcine intestinal ischemia model.

    Science.gov (United States)

    Takahashi, Tsuyoshi; Nakatsuka, Rie; Hara, Hisashi; Higashi, Shigeyoshi; Tanaka, Kouji; Miyazaki, Yasuhiro; Makino, Tomoki; Kurokawa, Yukinori; Yamasaki, Makoto; Takiguchi, Shuji; Mori, Masaki; Doki, Yuichiro; Nakajima, Kiyokazu

    2017-10-24

    Intestinal ischemia can lead to fatal complications if left unrecognized during surgery. The current techniques of intraoperative microvascular assessment remain subjective. Probe-based confocal laser endomicroscopy (pCLE) has the potential to objectively evaluate microvascular blood flow in real-time setting. The present study evaluated the technical feasibility of real-time intestinal bloodstream evaluation using pCLE in a porcine intestinal ischemia model. Seven pigs were used. The intestinal ischemia model was prepared by sequentially dividing the mesenteric blood vessels. The intestinal bloodstream was evaluated on its serosal surface using pCLE (Cellvizio 488 probe, Ultra Mini O) at every 1-cm segment from a vessel-preservation border (i.e., the cut end of the vessel). Images of the blood vessels and flow of red blood cells (RBCs) in each visualized vessel were semi-qualitatively assessed using a 3-scale scoring system. In addition, 25 surgeons blindly assessed the 10 movies recorded at 0, 1, 2, 3, and 5 cm from a vessel-preservation border using a 4-scale scoring system to confirm the consistency of the evaluation of the pCLE system. Images of the blood vessels were successfully obtained from the cut end of the vessel to the segment 4 cm away. Good unidirectional flow of RBCs was observed from the cut end to the 2-cm segment, whereas the flow became bidirectional between 2 and 3 cm segments. Beyond 4 cm, no flow images were obtained. The specimen obtained from the segment beyond 4 cm showed remarkable mucosal color change, which was confirmed as a necrotic change histologically. The evaluations from the cut end of the vessel to the segment 1 cm away by surgeons were excellent or good and it was almost consistent. Real-time bloodstream evaluation using pCLE is feasible and potentially effective for predicting intestinal ischemia during surgery.

  12. 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.

  13. 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.

  14. A UML Package for Specifying Real-Time Objects

    National Research Council Canada - National Science Library

    DiPippo, Lisa C; Ma, Lynn

    1999-01-01

    .... This paper presents a UML package for specifying real-time objects called RT-Object. The constructs in the package are based on the objects of the RTSORAC "Real-Time Semantic Objects Relationships And Constraints" model...

  15. 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

  16. 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.

  17. Parameter Estimation by Inverse Solution Methodology Using Genetic Algorithms for Real Time Temperature Prediction Model of Ladle Furnace

    National Research Council Canada - National Science Library

    Srinivas, Peri Subrahmanya; Kothari, Anil Kumar; Agrawal, Ashish

    2016-01-01

    .... In the present work, inverse methodology combined with Genetic Algorithms has been successfully employed for estimating parameter of a dynamic model aimed to predict liquid steel temperature in Ladle Furnace...

  18. AERIS - applications for the environment : real-time information synthesis : low emissions zone (LEZ) operational scenario modeling report.

    Science.gov (United States)

    2015-01-01

    This report describes the analysis and modeling effort that was conducted to simulate the potential : impacts of a Low Emissions Zone (LEZ) strategy. LEZs are designated areas within a metropolitan : region where special measures are implemented with...

  19. 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.

  20. AROME-WMED, a real-time mesoscale model designed for the HyMeX Special Observation Periods

    OpenAIRE

    Fourrié, N.; É. Bresson; M. Nuret; Jany, C; P. Brousseau; Doerenbecher, A.; Kreitz, M.; Nuissier, O.; E. Sevault; H. Bénichou; Amodei, M.; Pouponneau, F.

    2015-01-01

    During autumn 2012 and winter 2013, two Special Observation Periods (SOPs) of the Hydrological cycle in the Mediterranean Experiment (HyMeX) took place. For the preparatory studies and to support the instrument deployment during the field campaign, a dedicated version of the operational convective-scale AROME-France model was developed: the AROME-WMED model. It covers the western Mediterranean basin w...

  1. 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.

  2. 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.

  3. Real-time implementation of model predictive control on Maricopa-Stanfield irrigation and drainage district's WM canal

    Science.gov (United States)

    Water resources are limited in many agricultural areas. One method to improve the effective use of water is to improve delivery service from irrigation canals. This can be done by applying automatic control methods that control the gates in an irrigation canal. The model predictive control MPC is ...

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. Volitional and Real-Time Control Cursor Based on Eye Movement Decoding Using a Linear Decoding Model

    Directory of Open Access Journals (Sweden)

    Jinhua Zhang

    2016-01-01

    Full Text Available The aim of this study is to build a linear decoding model that reveals the relationship between the movement information and the EOG (electrooculogram data to online control a cursor continuously with blinks and eye pursuit movements. First of all, a blink detection method is proposed to reject a voluntary single eye blink or double-blink information from EOG. Then, a linear decoding model of time series is developed to predict the position of gaze, and the model parameters are calibrated by the RLS (Recursive Least Square algorithm; besides, the assessment of decoding accuracy is assessed through cross-validation procedure. Additionally, the subsection processing, increment control, and online calibration are presented to realize the online control. Finally, the technology is applied to the volitional and online control of a cursor to hit the multiple predefined targets. Experimental results show that the blink detection algorithm performs well with the voluntary blink detection rate over 95%. Through combining the merits of blinks and smooth pursuit movements, the movement information of eyes can be decoded in good conformity with the average Pearson correlation coefficient which is up to 0.9592, and all signal-to-noise ratios are greater than 0. The novel system allows people to successfully and economically control a cursor online with a hit rate of 98%.

  9. Physics-electrical hybrid model for real time impedance matching and remote plasma characterization in RF plasma sources

    Energy Technology Data Exchange (ETDEWEB)

    Sudhir, Dass, E-mail: dass.sudhir@iter-india.org; Bandyopadhyay, M.; Chakraborty, A. [ITER-India, Institute for Plasma Research, A-29 GIDC, Sec-25, Gandhinagar, 382016 Gujarat (India)

    2016-02-15

    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.

  10. Skill of Real-Time Operational Forecasts with the APCC Multi-Model Ensemble Prediction System for the Period of 2008-2015

    Science.gov (United States)

    Min, Young-Mi; Kryjov, Vladimir N.; Oh, Sang Myeong; Lee, Hyun-Ju

    2017-04-01

    This paper assesses the real-time one-month lead forecasts of three-month (seasonal) mean temperature and precipitation on a monthly basis issued by the Asia-Pacific Economic Cooperation (APEC) 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. The forecast skill for temperature is generally higher than that of precipitation. 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 2015/16 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 2012-14. In general, the skill of the real-time forecasts is close to that of historical ones. The regions, featuring the high skill of seasonal forecasts, feature lower interseasonal variability of skill characteristics than the regions of low skill.

  11. 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.

  12. 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.

  13. 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.

  14. Raman endoscopy for real time monitoring of anticancer drug treatment in colorectal tumors of live model mice

    Science.gov (United States)

    Taketani, Akinori; Ishigaki, Mika; Andriana, Bibin Bintan; Sato, Hidetoshi

    2014-02-01

    The aim of the present study is to evaluate the capability of a miniaturized Raman endoscope (mRE) system to monitor the advancement of colorectal tumors in live model mice. The endoscope is narrow enough to observe the inside of the mouse colon under anesthesia. The mRE system allows to observe the tissues and to apply a miniaturized Raman probe for the measurement at any targeted point within the colon. Raman spectroscopy allows obtaining information about molecular composition without damaging the tissue (i.e., noninvasively). Continuous monitoring of the same tumor is carried out to study molecular alterations along with its advancement. The Raman spectra measured before and after the anticancer drug (5-FU) treatment indicated spectral changes in the tumor tissue. It suggests that the tumor is not cured but supposedly transformed to another tumor type after the treatment.

  15. Predicting drowsy driving in real-time situations: Using an advanced driving simulator, accelerated failure time model, and virtual location-based services.

    Science.gov (United States)

    Wang, Junhua; Sun, Shuaiyi; Fang, Shouen; Fu, Ting; Stipancic, Joshua

    2017-02-01

    This paper aims to both identify the factors affecting driver drowsiness and to develop a real-time drowsy driving probability model based on virtual Location-Based Services (LBS) data obtained using a driving simulator. A driving simulation experiment was designed and conducted using 32 participant drivers. Collected data included the continuous driving time before detection of drowsiness and virtual LBS data related to temperature, time of day, lane width, average travel speed, driving time in heavy traffic, and driving time on different roadway types. Demographic information, such as nap habit, age, gender, and driving experience was also collected through questionnaires distributed to the participants. An Accelerated Failure Time (AFT) model was developed to estimate the driving time before detection of drowsiness. The results of the AFT model showed driving time before drowsiness was longer during the day than at night, and was longer at lower temperatures. Additionally, drivers who identified as having a nap habit were more vulnerable to drowsiness. Generally, higher average travel speeds were correlated to a higher risk of drowsy driving, as were longer periods of low-speed driving in traffic jam conditions. Considering different road types, drivers felt drowsy more quickly on freeways compared to other facilities. The proposed model provides a better understanding of how driver drowsiness is influenced by different environmental and demographic factors. The model can be used to provide real-time data for the LBS-based drowsy driving warning system, improving past methods based only on a fixed driving. Copyright © 2016 Elsevier Ltd. All rights reserved.

  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. 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.

  18. 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)

  19. Non-invasive volumetric optoacoustic imaging of cardiac cycles in acute myocardial infarction model in real-time

    Science.gov (United States)

    Lin, Hasiao-Chun Amy; Déan-Ben, Xosé Luís.; Kimm, Melanie; Kosanke, Katja; Haas, Helena; Meier, Reinhard; Lohöfer, Fabian; Wildgruber, Moritz; Razansky, Daniel

    2017-03-01

    Extraction of murine cardiac functional parameters on a beat-by-beat basis remains challenging with the existing imaging modalities. Novel methods enabling in vivo characterization of functional parameters at a high temporal resolution are poised to advance cardiovascular research and provide a better understanding of the mechanisms underlying cardiac diseases. We present a new approach based on analyzing contrast-enhanced optoacoustic (OA) images acquired at high volumetric frame rate without using cardiac gating or other approaches for motion correction. Acute myocardial infarction was surgically induced in murine models, and the method was modified to optimize for acquisition of artifact-free optoacoustic data. Infarcted hearts could be differentiated from healthy controls based on a significantly higher pulmonary transit time (PTT: infarct 2.07 s vs. healthy 1.34 s), while no statistically significant difference was observed in the heart rate (318 bpm vs. 309 bpm). In combination with the proven ability of optoacoustics to track targeted probes within the injured myocardium, our method is capable of depicting cardiac anatomy, function, and molecular signatures on a beat-by-beat basis, both with high spatial and temporal resolution, thus providing new insights into the study of myocardial ischemia.

  20. Modeling and Validating Time, Buffering, and Utilization of a Large-Scale, Real-Time Data Acquisition System

    CERN Document Server

    Santos, Alejandro; The ATLAS collaboration

    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...

  1. Modeling and Validating Time, Buffering, and Utilization of a Large-Scale, Real-Time Data Acquisition System

    CERN Document Server

    Santos, Alejandro; The ATLAS collaboration

    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 ...

  2. A UWB Radar Signal Processing Platform for Real-Time Human Respiratory Feature Extraction Based on Four-Segment Linear Waveform Model.

    Science.gov (United States)

    Hsieh, Chi-Hsuan; Chiu, Yu-Fang; Shen, Yi-Hsiang; Chu, Ta-Shun; Huang, Yuan-Hao

    2016-02-01

    This paper presents an ultra-wideband (UWB) impulse-radio radar signal processing platform used to analyze human respiratory features. Conventional radar systems used in human detection only analyze human respiration rates or the response of a target. However, additional respiratory signal information is available that has not been explored using radar detection. The authors previously proposed a modified raised cosine waveform (MRCW) respiration model and an iterative correlation search algorithm that could acquire additional respiratory features such as the inspiration and expiration speeds, respiration intensity, and respiration holding ratio. To realize real-time respiratory feature extraction by using the proposed UWB signal processing platform, this paper proposes a new four-segment linear waveform (FSLW) respiration model. This model offers a superior fit to the measured respiration signal compared with the MRCW model and decreases the computational complexity of feature extraction. In addition, an early-terminated iterative correlation search algorithm is presented, substantially decreasing the computational complexity and yielding negligible performance degradation. These extracted features can be considered the compressed signals used to decrease the amount of data storage required for use in long-term medical monitoring systems and can also be used in clinical diagnosis. The proposed respiratory feature extraction algorithm was designed and implemented using the proposed UWB radar signal processing platform including a radar front-end chip and an FPGA chip. The proposed radar system can detect human respiration rates at 0.1 to 1 Hz and facilitates the real-time analysis of the respiratory features of each respiration period.

  3. Workstation-Based Real-Time Mesoscale Modeling Designed for Weather Support to Operations at the Kennedy Space Center and Cape Canaveral Air Station

    Science.gov (United States)

    Manobianco, John; Zack, John W.; Taylor, Gregory E.

    1996-01-01

    This paper describes the capabilities and operational utility of a version of the Mesoscale Atmospheric Simulation System (MASS) that has been developed to support operational weather forecasting at the Kennedy Space Center (KSC) and Cape Canaveral Air Station (CCAS). The implementation of local, mesoscale modeling systems at KSC/CCAS is designed to provide detailed short-range (less than 24 h) forecasts of winds, clouds, and hazardous weather such as thunderstorms. Short-range forecasting is a challenge for daily operations, and manned and unmanned launches since KSC/CCAS is located in central Florida where the weather during the warm season is dominated by mesoscale circulations like the sea breeze. For this application, MASS has been modified to run on a Stardent 3000 workstation. Workstation-based, real-time numerical modeling requires a compromise between the requirement to run the system fast enough so that the output can be used before expiration balanced against the desire to improve the simulations by increasing resolution and using more detailed physical parameterizations. It is now feasible to run high-resolution mesoscale models such as MASS on local workstations to provide timely forecasts at a fraction of the cost required to run these models on mainframe supercomputers. MASS has been running in the Applied Meteorology Unit (AMU) at KSC/CCAS since January 1994 for the purpose of system evaluation. In March 1995, the AMU began sending real-time MASS output to the forecasters and meteorologists at CCAS, Spaceflight Meteorology Group (Johnson Space Center, Houston, Texas), and the National Weather Service (Melbourne, Florida). However, MASS is not yet an operational system. The final decision whether to transition MASS for operational use will depend on a combination of forecaster feedback, the AMU's final evaluation results, and the life-cycle costs of the operational system.

  4. 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

  5. Model documentation for relations between continuous real-time and discrete water-quality constituents in Indian Creek, Johnson County, Kansas, June 2004 through May 2013

    Science.gov (United States)

    Stone, Mandy L.; Graham, Jennifer L.

    2014-01-01

    Johnson County is the fastest growing county in Kansas, with a population of about 560,000 people in 2012. Urban growth and development can have substantial effects on water quality, and streams in Johnson County are affected by nonpoint-source pollutants from stormwater runoff and point-source discharges such as municipal wastewater effluent. Understanding of current (2014) water-quality conditions and the effects of urbanization is critical for the protection and remediation of aquatic resources in Johnson County, Kansas and downstream reaches located elsewhere. The Indian Creek Basin is 194 square kilometers and includes parts of Johnson County, Kansas and Jackson County, Missouri. Approximately 86 percent of the Indian Creek Basin is located in Johnson County, Kansas. The U.S. Geological Survey, in cooperation with Johnson County Wastewater, operated a series of six continuous real-time water-quality monitoring stations in the Indian Creek Basin during June 2011 through May 2013; one of these sites has been operating since February 2004. Five monitoring sites were located on Indian Creek and one site was located on Tomahawk Creek. The purpose of this report is to document regression models that establish relations between continuously measured water-quality properties and discretely collected water-quality constituents. Continuously measured water-quality properties include streamflow, specific conductance, pH, water temperature, dissolved oxygen, turbidity, and nitrate. Discrete water-quality samples were collected during June 2011 through May 2013 at five new sites and June 2004 through May 2013 at a long-term site and analyzed for sediment, nutrients, bacteria, and other water-quality constituents. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physical properties to estimate concentrations of those constituents of interest that are not easily measured in real time

  6. 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

  7. Real-Time Mesoscale Prediction on workstations.

    Science.gov (United States)

    Cotton, William R.; Thompson, Gregory; Mieike, Paul W., Jr.

    1994-03-01

    Experience in performing real-time mesoscale numerical prediction forecasts using the Regional Atmospheric Modeling System (RAMS) over Colorado for a winter season on high-performance workstations is summarized. Performance evaluation is done for specific case studies and, statistically, for the entire winter season. RAMS forecasts are also compared with nested grid model forecasts. In addition, RAMS precipitation forecasts with a simple "dump bucket" scheme are compared with explicit, bulk microphysics parameterization schemes. The potential applications and political/ social problems of having a readily accessible, real-time mesoscale forecasting capability on low-cost, high-performance workstations is discussed.

  8. 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.

  9. International journal of computational fluid dynamics real-time prediction of unsteady flow based on POD reduced-order model and particle filter

    Science.gov (United States)

    Kikuchi, Ryota; Misaka, Takashi; Obayashi, Shigeru

    2016-04-01

    An integrated method consisting of a proper orthogonal decomposition (POD)-based reduced-order model (ROM) and a particle filter (PF) is proposed for real-time prediction of an unsteady flow field. The proposed method is validated using identical twin experiments of an unsteady flow field around a circular cylinder for Reynolds numbers of 100 and 1000. In this study, a PF is employed (ROM-PF) to modify the temporal coefficient of the ROM based on observation data because the prediction capability of the ROM alone is limited due to the stability issue. The proposed method reproduces the unsteady flow field several orders faster than a reference numerical simulation based on Navier-Stokes equations. Furthermore, the effects of parameters, related to observation and simulation, on the prediction accuracy are studied. Most of the energy modes of the unsteady flow field are captured, and it is possible to stably predict the long-term evolution with ROM-PF.

  10. Modeling of 5 ' nuclease real-time responses for optimization of a high-throughput enrichment PCR procedure for Salmonella enterica

    DEFF Research Database (Denmark)

    Knutsson, R.; Löfström, Charlotta; Grage, H.

    2002-01-01

    The performance of a 5' nuclease real-time PCR assay was studied to optimize an automated method of detection of preenriched Salmonella enterica cells in buffered peptone water (BPW). The concentrations and interactions of the PCR reagents were evaluated on the basis of two detection responses......, the threshold cycle (C-T) and the fluorescence intensity by a normalized reporter value (DeltaR(n)). The C-r response was identified as the most suitable for detection modeling to describe the PCR performances of different samples. DNA extracted from S. enterica serovar Enteritidis was studied in double....../microwell for the AmpliTaq Gold mixture. To verify the improved amplification capacity of the rTth mixture, BPW was inoculated with 1 CFU of S. enterica serovar Enteritidis per ml and the mixture was incubated at 30degreesC. Samples for PCR were withdrawn every 4 h during a 36-h enrichment. Use of the rTth mixture...

  11. 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.

  12. 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

  13. Conditional Inducible Triple-Transgenic Mouse Model for Rapid Real-Time Detection of HCV NS3/4A Protease Activity

    Science.gov (United States)

    Yang, Jing; Zhao, Haiwei; Qiao, Qinghua; Han, Peijun; Xu, Zhikai; Yin, Wen

    2016-01-01

    Hepatitis C virus (HCV) frequently establishes persistent infections that can develop into severe liver disease. The HCV NS3/4A serine protease is not only essential for viral replication but also cleaves multiple cellular targets that block downstream interferon activation. Therefore, NS3/4A is an ideal target for the development of anti-HCV drugs and inhibitors. In the current study, we generated a novel NS3/4A/Lap/LC-1 triple-transgenic mouse model that can be used to evaluate and screen NS3/4A protease inhibitors. The NS3/4A protease could be conditionally inducibly expressed in the livers of the triple-transgenic mice using a dual Tet-On and Cre/loxP system. In this system, doxycycline (Dox) induction resulted in the secretion of Gaussia luciferase (Gluc) into the blood, and this secretion was dependent on NS3/4A protease-mediated cleavage at the 4B5A junction. Accordingly, NS3/4A protease activity could be quickly assessed in real time simply by monitoring Gluc activity in plasma. The results from such monitoring showed a 70-fold increase in Gluc activity levels in plasma samples collected from the triple-transgenic mice after Dox induction. Additionally, this enhanced plasma Gluc activity was well correlated with the induction of NS3/4A protease expression in the liver. Following oral administration of the commercial NS3/4A-specific inhibitors telaprevir and boceprevir, plasma Gluc activity was reduced by 50% and 65%, respectively. Overall, our novel transgenic mouse model offers a rapid real-time method to evaluate and screen potential NS3/4A protease inhibitors. PMID:26943641

  14. Development of Energy and Reserve Pre-dispatch and Re-dispatch Models for Real-time Price Risk and Reliability Assessment

    DEFF Research Database (Denmark)

    Ding, Yi; Xie, Min; Wu, Qiuwei

    2014-01-01

    -dispatch, load curtailment as well as real-time electricity prices. The modified IEEE-RTS has been analyzed to illustrate the techniques. The proposed market scheme coupled with a contingency analysis methodology has been used to evaluate both real-time electricity price risk and short term reliabilities during...

  15. UML for real design of embedded real-time systems

    CERN Document Server

    Martin, Grant; Selic, Bran

    2003-01-01

    Models, Software Models and UML.- UML for Real-Time.- Structural Modeling with UML 2.0.- Message Sequence Charts.- UML and Platform-based Design.- UML for Hardware and Software Object Modeling.- Fine Grained Patterns for Real-Time Systems.- Architectural Patterns for Real-Time Systems.- Modeling Quality of Service with UML.- Modeling Metric Time.- Performance Analysis with UML.- Schedulability Analysis with UML.- Automotive UML.- Specifying Telecommunications Systems with UML.- Leveraging UML to Deliver Correct Telecom Applications.- Software Performance Engineering.

  16. Estimating crop yields by integrating the FAO Crop Specific Water Balance model with real-time satellite data and ground-based ancillary data

    Science.gov (United States)

    Reynolds, Curt Andrew

    The broad objective of this research was to develop a spatial model which provides both timely and quantitative regional maize yield estimates for real-time Early Warning Systems (EWS) by integrating satellite data with ground-based ancillary data. The Food and Agriculture Organization (FAO) Crop Specific Water Balance (CSWB) model was modified by using the real-time spatial data that include: dekad (ten-day) estimated rainfall (RFE) and Normalized Difference Vegetation Index (NDVI) composites derived from the METEOSAT and NOAA-AVHRR satellites, respectively; ground-based dekad potential evapo-transpiration (PET) data and seasonal estimated area-planted data provided by the Government of Kenya (GoK). A Geographical Information System (GIS) software was utilized to: drive the crop yield model; manage the spatial and temporal variability of the satellite images; interpolate between ground-based potential evapo-transpiration and rainfall measurements; and import ancillary data such as soil maps, administrative boundaries, etc. In addition, agro-ecological zones, length of growing season, and crop production functions, as defined by the FAO, were utilized to estimate quantitative maize yields. The GIS-based CSWB model was developed for three different resolutions: agro-ecological zone (AEZ) polygons; 7.6-kilometer pixels; and 1.1-kilometer pixels. The model was validated by comparing model production estimates from archived satellite and agro-meteorological data to historical district maize production reports from two Kenya government agencies, the Ministry of Agriculture (MoA) and the Department of Resource Surveys and Remote Sensing (DRSRS). For the AEZ analysis, comparison of model district maize production results and district maize production estimates from the MoA (1989-1997) and the DRSRS (1989-1993) revealed correlation coefficients of 0.94 and 0.93, respectively. The comparison for the 7.6-kilometer analysis showed correlation coefficients of 0.95 and 0

  17. 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.

  18. 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.

  19. Demonstration of a very inexpensive, turbidimetric, real-time, RT-LAMP detection platform using shrimp Laem-Singh virus (LSNV) as a model.

    Science.gov (United States)

    Arunrut, Narong; Suebsing, Rungkarn; Withyachumnarnkul, Boonsirm; Kiatpathomchai, Wansika

    2014-01-01

    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.

  20. 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.

  1. Two-photon microscopy for real-time monitoring of focused ultrasound-mediated drug delivery to the brain in a mouse model of Alzheimer's disease

    Science.gov (United States)

    Burgess, Alison; Eterman, Naomi; Aubert, Isabelle; Hynynen, Kullervo

    2013-02-01

    There is substantial evidence that focused ultrasound (FUS) in combination with microbubble contrast agent can cause disruption of the blood-brain barrier (BBB) to aid in drug delivery to the brain. We have previously demonstrated that FUS efficiently delivers antibodies against amyloid-β peptides (Aβ) through the BBB, leading to a reduction in amyloid pathology at 4 days in a mouse model of Alzheimer's disease. In the current study, we used two-photon microscopy to characterize the effect of FUS in real time on amyloid pathology in the mouse brain. Mice were anesthetized and a cranial window was made in the skull. A custom-built ultrasound transducer was fixed to a coverslip and attached to the skull, covering the cranial window. Methoxy-X04 [2-5mg/kg] delivered intravenously 1 hr prior to the experiment clearly labelled the Aβ surrounding the vessels and the amyloid plaques in the cortex. Dextran conjugated Texas Red (70kDa) administered intravenously, confirmed BBB disruption. BBB disruption occurred in transgenic and non-transgenic animals at similar ultrasound pressures tested. However, the time required for BBB closure following FUS was longer in the Tg mice. We have conjugated Aβ antibodies to the fluorescent molecule FITC for real time monitoring of the antibody distribution in the brain. Our current experiments are aimed at optimizing the parameters to achieve maximal fluorescent intensity of the BAM10 antibody at the plaque surface. Two-photon microscopy has proven to be a valuable tool for evaluating the efficacy of FUS mediated drug delivery, including antibodies, to the Alzheimer brain.

  2. Forecast skill of a high-resolution real-time mesoscale model designed for weather support of operations at Kennedy Space Center and Cape Canaveral Air Station

    Science.gov (United States)

    Taylor, Gregory E.; Zack, John W.; Manobianco, John

    1994-01-01

    NASA funded Mesoscale Environmental Simulations and Operations (MESO), Inc. to develop a version of the Mesoscale Atmospheric Simulation System (MASS). The model has been modified specifically for short-range forecasting in the vicinity of KSC/CCAS. To accomplish this, the model domain has been limited to increase the number of horizontal grid points (and therefore grid resolution) and the model' s treatment of precipitation, radiation, and surface hydrology physics has been enhanced to predict convection forced by local variations in surface heat, moisture fluxes, and cloud shading. The objective of this paper is to (1) provide an overview of MASS including the real-time initialization and configuration for running the data pre-processor and model, and (2) to summarize the preliminary evaluation of the model's forecasts of temperature, moisture, and wind at selected rawinsonde station locations during February 1994 and July 1994. MASS is a hydrostatic, three-dimensional modeling system which includes schemes to represent planetary boundary layer processes, surface energy and moisture budgets, free atmospheric long and short wave radiation, cloud microphysics, and sub-grid scale moist convection.

  3. 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

  4. 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.

    Science.gov (United States)

    Bælum, Jacob; Prestat, Emmanuel; David, Maude M; Strobel, Bjarne W; Jacobsen, Carsten S

    2012-08-01

    Mineralization potentials, rates, and kinetics of the three phenoxy acid (PA) herbicides, 2,4-dichlorophenoxyacetic acid (2,4-D), 4-chloro-2-methylphenoxyacetic acid (MCPA), and 2-(4-chloro-2-methylphenoxy)propanoic acid (MCPP), were investigated and compared in 15 soils collected from five 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 the genetic potential for degrading PA in the soils. In 25 of the 45 mineralization scenarios, ∼60% mineralization was observed within 118 days. Elevated concentrations of tfdA in the range 1 × 10(5) to 5 × 10(7) gene copies g(-1) of soil were observed in soils where mineralization could be described by using growth-linked kinetic models. A clear trend was observed that the mineralization rates of the three PAs occurred in the order 2,4-D > MCPA > MCPP, and a correlation was observed between rapid mineralization and soils exposed to PA previously. Finally, for 2,4-D mineralization, all seven mineralization patterns which were best fitted by the exponential model yielded a higher tfdA gene potential after mineralization had occurred than the three mineralization patterns best fitted by the Lin model.

  5. Acting to gain information: Real-time reasoning meets real-time perception

    Science.gov (United States)

    Rosenschein, Stan

    1994-01-01

    Recent advances in intelligent reactive systems suggest new approaches to the problem of deriving task-relevant information from perceptual systems in real time. The author will describe work in progress aimed at coupling intelligent control mechanisms to real-time perception systems, with special emphasis on frame rate visual measurement systems. A model for integrated reasoning and perception will be discussed, and recent progress in applying these ideas to problems of sensor utilization for efficient recognition and tracking will be described.

  6. Accident diagnosis of the Angra-2 nuclear power plant based on intelligent real-time acquisition agents and a logical tree model

    Energy Technology Data Exchange (ETDEWEB)

    Paiva, Gustavo V.; Schirru, Roberto, E-mail: gustavopaiva@poli.ufrj.br, E-mail: schirru@lmp.ufrj.br [Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Departamento de Engenharia Nuclear

    2017-07-01

    This work aims to create a model and a prototype, using the Python language, which with the application of an Expert System uses production rules to analyze the data obtained in real time from the plant and help the operator to identify the occurrence of transients / accidents. In the event of a transient, the program alerts the operator and indicates which section of the Operation Manual should be consulted to bring the plant back to its normal state. The generic structure used to represent the knowledge of the Expert System was a Fault Tree and the data obtained from the plant was done through intelligent acquisition agents that transform the data obtained from the plant into Boolean values used in the Fault Tree, including the use of Fuzzy Logic. In order to test the program, a simplified model of the Almirante Alvaro Alberto 2 Nuclear Power Plant (Angra-2) manuals was used and with this model, simulations were performed to analyze the program's operation and if it leads to the expected results. The results of the tests presented a quick identification of the events and great accuracy, demonstrating the applicability of the model to the problem. (author)

  7. Using a Novel In Vitro Fontan Model and Condition-Specific Real-Time MRI Data to Examine Hemodynamic Effects of Respiration and Exercise.

    Science.gov (United States)

    Tree, Michael; Wei, Zhenglun Alan; Trusty, Phillip M; Raghav, Vrishank; Fogel, Mark; Maher, Kevin; Yoganathan, Ajit

    2017-10-24

    Several studies exist modeling the Fontan connection to understand its hemodynamic ties to patient outcomes (Chopski in: Experimental and Computational Assessment of Mechanical Circulatory Assistance of a Patient-Specific Fontan Vessel Configuration. Dissertation, 2013; Khiabani et al. in J Biomech 45:2376-2381, 2012; Taylor and Figueroa in Annu Rev Biomed 11:109-134, 2009; Vukicevic et al. in ASAIO J 59:253-260, 2013). The most patient-accurate of these studies include flexible, patient-specific total cavopulmonary connections. This study improves Fontan hemodynamic modeling by validating Fontan model flexibility against a patient-specific bulk compliance value, and employing real-time phase contrast magnetic resonance flow data. The improved model was employed to acquire velocity field information under breath-held, free-breathing, and exercise conditions to investigate the effect of these conditions on clinically important Fontan hemodynamic metrics including power loss and viscous dissipation rate. The velocity data, obtained by stereoscopic particle image velocimetry, was visualized for qualitative three-dimensional flow field comparisons between the conditions. Key hemodynamic metrics were calculated from the velocity data and used to quantitatively compare the flow conditions. The data shows a multi-factorial and extremely patient-specific nature to Fontan hemodynamics.

  8. 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

  9. Real Time Sonic Boom Display

    Science.gov (United States)

    Haering, Ed

    2014-01-01

    This presentation will provide general information about sonic boom mitigation technology to the public in order to supply information to potential partners and licensees. The technology is a combination of flight data, atmospheric data and terrain information implemented into a control room real time display for flight planning. This research is currently being performed and as such, any results and conclusions are ongoing.

  10. Real Time Control on Firewire

    NARCIS (Netherlands)

    Zhang, Yuchen

    2004-01-01

    The goal of this project is to get insight into the use of Firewire as a field bus for real-time control. A characterization of Firewire's asynchronous transmission has been made by testing the point-to-point roundtrip in a 3-node Firewire network. The results show Firewire's asynchronous

  11. 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.

  12. 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...

  13. ISTTOK real-time architecture

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-03-15

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

  14. Using hierarchical Bayesian binary probit models to analyze crash injury severity on high speed facilities with real-time traffic data.

    Science.gov (United States)

    Yu, Rongjie; Abdel-Aty, Mohamed

    2014-01-01

    Severe crashes are causing serious social and economic loss, and because of this, reducing crash injury severity has become one of the key objectives of the high speed facilities' (freeway and expressway) management. Traditional crash injury severity analysis utilized data mainly from crash reports concerning the crash occurrence information, drivers' characteristics and roadway geometric related variables. In this study, real-time traffic and weather data were introduced to analyze the crash injury severity. The space mean speeds captured by the Automatic Vehicle Identification (AVI) system on the two roadways were used as explanatory variables in this study; and data from a mountainous freeway (I-70 in Colorado) and an urban expressway (State Road 408 in Orlando) have been used to identify the analysis result's consistence. Binary probit (BP) models were estimated to classify the non-severe (property damage only) crashes and severe (injury and fatality) crashes. Firstly, Bayesian BP models' results were compared to the results from Maximum Likelihood Estimation BP models and it was concluded that Bayesian inference was superior with more significant variables. Then different levels of hierarchical Bayesian BP models were developed with random effects accounting for the unobserved heterogeneity at segment level and crash individual level, respectively. Modeling results from both studied locations demonstrate that large variations of speed prior to the crash occurrence would increase the likelihood of severe crash occurrence. Moreover, with considering unobserved heterogeneity in the Bayesian BP models, the model goodness-of-fit has improved substantially. Finally, possible future applications of the model results and the hierarchical Bayesian probit models were discussed. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Selection of reference genes for quantitative real-time reverse transcription-polymerase chain reaction in concanavalin A-induced hepatitis model.

    Science.gov (United States)

    Shi, Guojun; Zhang, Zhijian; Feng, Dechun; Xu, Yan; Lu, Yan; Wang, Jiqiu; Jiang, Jingjing; Zhang, Zhiguo; Li, Xiaoying; Ning, Guang

    2010-06-01

    Quantitative real-time reverse transcription-polymerase chain reaction (Q-PCR) has become an indispensable technique for accurate determination of gene expression in various samples. In mice, intravenous injection of concanavalin A (ConA) leads to acute hepatitis and liver injury. Functional studies based on this model have provided insights for understanding the mechanisms of liver injury. However, no data have been reported to validate reference genes during the progression of ConA-induced hepatitis (CIH). In this study, IkappaBalpha and C/EBPbeta messenger RNA (mRNA) levels were examined using Q-PCR with ACTB as the reference gene after ConA injection. However, we got inconsistent results with previous reports determining IkappaBalpha and C/EBPbeta mRNA expression levels. The results indicate the necessity for stability analysis of candidate reference genes in the CIH model. geNorm, NormFinder, and BestKeeper software analysis indicates that ACTB is the most unstable gene during CIH progression among the 10 reference genes tested, whereas RPLP0 or HPRT1 is the most stable one. This study demonstrates that some of the commonly used reference genes are inadequate for normalization of Q-PCR data due to their expression instability. Furthermore, this study validates HPRT1 and RPLP0 as appropriate reference genes for Q-PCR analysis in the CIH model. Copyright 2010 Elsevier Inc. All rights reserved.

  16. A Unified Trading Model Based on Robust Optimization for Day-Ahead and Real-Time Markets with Wind Power Integration

    National Research Council Canada - National Science Library

    Yuewen Jiang; Meisen Chen; Shi You

    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...

  17. Refinement of regression models to estimate real-time concentrations of contaminants in the Menomonee River drainage basin, southeast Wisconsin, 2008-11

    Science.gov (United States)

    Baldwin, Austin K.; Robertson, Dale M.; Saad, David A.; Magruder, Christopher

    2013-01-01

    In 2008, the U.S. Geological Survey and the Milwaukee Metropolitan Sewerage District initiated a study to develop regression models to estimate real-time concentrations and loads of chloride, suspended solids, phosphorus, and bacteria in streams near Milwaukee, Wisconsin. To collect monitoring data for calibration of models, water-quality sensors and automated samplers were installed at six sites in the Menomonee River drainage basin. The sensors continuously measured four potential explanatory variables: water temperature, specific conductance, dissolved oxygen, and turbidity. Discrete water-quality samples were collected and analyzed for five response variables: chloride, total suspended solids, total phosphorus, Escherichia coli bacteria, and fecal coliform bacteria. Using the first year of data, regression models were developed to continuously estimate the response variables on the basis of the continuously measured explanatory variables. Those models were published in a previous report. In this report, those models are refined using 2 years of additional data, and the relative improvement in model predictability is discussed. In addition, a set of regression models is presented for a new site in the Menomonee River Basin, Underwood Creek at Wauwatosa. The refined models use the same explanatory variables as the original models. The chloride models all used specific conductance as the explanatory variable, except for the model for the Little Menomonee River near Freistadt, which used both specific conductance and turbidity. Total suspended solids and total phosphorus models used turbidity as the only explanatory variable, and bacteria models used water temperature and turbidity as explanatory variables. An analysis of covariance (ANCOVA), used to compare the coefficients in the original models to those in the refined models calibrated using all of the data, showed that only 3 of the 25 original models changed significantly. Root-mean-squared errors (RMSEs

  18. Real Time Grid Reliability Management 2005

    Energy Technology Data Exchange (ETDEWEB)

    Eto, Joe; Eto, Joe; Lesieutre, Bernard; Lewis, Nancy Jo; Parashar, Manu

    2008-07-07

    The increased need to manage California?s electricity grid in real time is a result of the ongoing transition from a system operated by vertically-integrated utilities serving native loads to one operated by an independent system operator supporting competitive energy markets. During this transition period, the traditional approach to reliability management -- construction of new transmission lines -- has not been pursued due to unresolved issues related to the financing and recovery of transmission project costs. In the absence of investments in new transmission infrastructure, the best strategy for managing reliability is to equip system operators with better real-time information about actual operating margins so that they can better understand and manage the risk of operating closer to the edge. A companion strategy is to address known deficiencies in offline modeling tools that are needed to ground the use of improved real-time tools. This project: (1) developed and conducted first-ever demonstrations of two prototype real-time software tools for voltage security assessment and phasor monitoring; and (2) prepared a scoping study on improving load and generator response models. Additional funding through two separate subsequent work authorizations has already been provided to build upon the work initiated in this project.

  19. On epidemic modeling in real time: An application to the 2009 Novel A (H1N1 influenza outbreak in Canada

    Directory of Open Access Journals (Sweden)

    Fisman David N

    2010-11-01

    Full Text Available Abstract Background Management of emerging infectious diseases such as the 2009 influenza pandemic A (H1N1 poses great challenges for real-time mathematical modeling of disease transmission due to limited information on disease natural history and epidemiology, stochastic variation in the course of epidemics, and changing case definitions and surveillance practices. Findings The Richards model and its variants are used to fit the cumulative epidemic curve for laboratory-confirmed pandemic H1N1 (pH1N1 infections in Canada, made available by the Public Health Agency of Canada (PHAC. The model is used to obtain estimates for turning points in the initial outbreak, the basic reproductive number (R0, and for expected final outbreak size in the absence of interventions. Confirmed case data were used to construct a best-fit 2-phase model with three turning points. R0 was estimated to be 1.30 (95% CI 1.12-1.47 for the first phase (April 1 to May 4 and 1.35 (95% CI 1.16-1.54 for the second phase (May 4 to June 19. Hospitalization data were also used to fit a 1-phase model with R0 = 1.35 (1.20-1.49 and a single turning point of June 11. Conclusions Application of the Richards model to Canadian pH1N1 data shows that detection of turning points is affected by the quality of data available at the time of data usage. Using a Richards model, robust estimates of R0 were obtained approximately one month after the initial outbreak in the case of 2009 A (H1N1 in Canada.

  20. Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model.

    Science.gov (United States)

    Byrne, Michael F; Chapados, Nicolas; Soudan, Florian; Oertel, Clemens; Linares Pérez, Milagros; Kelly, Raymond; Iqbal, Nadeem; Chandelier, Florent; Rex, Douglas K

    2017-10-24

    In general, academic but not community endoscopists have demonstrated adequate endoscopic differentiation accuracy to make the 'resect and discard' paradigm for diminutive colorectal polyps workable. Computer analysis of video could potentially eliminate the obstacle of interobserver variability in endoscopic polyp interpretation and enable widespread acceptance of 'resect and discard'. We developed an artificial intelligence (AI) model for real-time assessment of endoscopic video images of colorectal polyps. A deep convolutional neural network model was used. Only narrow band imaging video frames were used, split equally between relevant multiclasses. Unaltered videos from routine exams not specifically designed or adapted for AI classification were used to train and validate the model. The model was tested on a separate series of 125 videos of consecutively encountered diminutive polyps that were proven to be adenomas or hyperplastic polyps. The AI model works with a confidence mechanism and did not generate sufficient confidence to predict the histology of 19 polyps in the test set, representing 15% of the polyps. For the remaining 106 diminutive polyps, the accuracy of the model was 94% (95% CI 86% to 97%), the sensitivity for identification of adenomas was 98% (95% CI 92% to 100%), specificity was 83% (95% CI 67% to 93%), negative predictive value 97% and positive predictive value 90%. An AI model trained on endoscopic video can differentiate diminutive adenomas from hyperplastic polyps with high accuracy. Additional study of this programme in a live patient clinical trial setting to address resect and discard is planned. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  1. Multicolor in vivo targeted imaging to guide real-time surgery of HER2-positive micrometastases in a two-tumor coincident model of ovarian cancer.

    Science.gov (United States)

    Longmire, Michelle; Kosaka, Nobuyuki; Ogawa, Mikako; Choyke, Peter L; Kobayashi, Hisataka

    2009-06-01

    One of the primary goals of oncological molecular imaging is to accurately identify and characterize malignant tissues in vivo. Currently, molecular imaging relies on targeting a single molecule that while overexpressed in malignancy, is often also expressed at lower levels in normal tissue, resulting in reduced tumor to background ratios. One approach to increasing the specificity of molecular imaging in cancer is to use multiple probes each with distinct fluorescence to target several surface antigens simultaneously, in order to identify tissue expression profiles, rather than relying on the expression of a single target. This next step forward in molecular imaging will rely on characterization of tissue based on fluorescence and therefore will require the ability to simultaneously identify several optical probes each attached to different targeting ligands. We created a novel 'coincident' ovarian cancer mouse model by coinjecting each animal with two distinct cell lines, HER2+/red fluorescent protein (RFP)- SKOV3 and HER2-/RFP+ SHIN3-RFP, in order to establish a model of disease in which animals simultaneously bore tumors with two distinct phenotypes (HER2+/RFP-, HER2-/RFP+), which could be utilized for multicolor imaging. The HER2 receptor of the SKOV3 cell line was targeted with a trastuzumab-rhodamine green conjugate to create green tumor implants, whereas the RFP plasmid of the SHIN3 cells created red tumor implants. We demonstrate that real-time in vivo multicolor imaging is feasible and that fluorescence characteristics can then serve to guide the surgical removal of disease.

  2. Microarray-driven validation of reference genes for quantitative real-time polymerase chain reaction in a rat vocal fold model of mucosal injury.

    Science.gov (United States)

    Chang, Zhen; Ling, Changying; Yamashita, Masaru; Welham, Nathan V

    2010-11-15

    Relative quantification by normalization against a stably expressed reference gene is a widely used data analysis method in microarray and quantitative real-time polymerase chain reaction (qRT-PCR) platforms; however, recent evidence suggests that many commonly utilized reference genes are unstable in certain experimental systems and situations. The primary aim of this study, therefore, was to screen and identify stably expressed reference genes in a well-established rat model of vocal fold mucosal injury. We selected and evaluated the expression stability of nine candidate reference genes. Ablim1, Sptbn1, and Wrnip1 were identified as stably expressed in a model-specific microarray dataset and were further validated as suitable reference genes in an independent qRT-PCR experiment using 2(-DeltaCT) and pairwise comparison-based (geNorm) analyses. Parallel analysis of six commonly used reference genes identified Sdha as the only stably expressed candidate in this group. Sdha, Sptbn1, and the geometric mean of Sdha and Sptbn1 each provided accurate normalization of target gene Tgfb1; Gapdh, the least stable candidate gene in our dataset, provided inaccurate normalization and an invalid experimental result. The stable reference genes identified here are suitable for accurate normalization of target gene expression in vocal fold mucosal injury experiments. Copyright 2010 Elsevier Inc. All rights reserved.

  3. Real-time PCR expression profiling of genes encoding potential virulence factors in Candida albicans biofilms: identification of model-dependent and -independent gene expression

    Directory of Open Access Journals (Sweden)

    Řičicová Markéta

    2010-04-01

    Full Text Available Abstract Background Candida albicans infections are often associated with biofilm formation. Previous work demonstrated that the expression of HWP1 (hyphal wall protein and of genes belonging to the ALS (agglutinin-like sequence, SAP (secreted aspartyl protease, PLB (phospholipase B and LIP (lipase gene families is associated with biofilm growth on mucosal surfaces. We investigated using real-time PCR whether genes encoding potential virulence factors are also highly expressed in biofilms associated with abiotic surfaces. For this, C. albicans biofilms were grown on silicone in microtiter plates (MTP or in the Centres for Disease Control (CDC reactor, on polyurethane in an in vivo subcutaneous catheter rat (SCR model, and on mucosal surfaces in the reconstituted human epithelium (RHE model. Results HWP1 and genes belonging to the ALS, SAP, PLB and LIP gene families were constitutively expressed in C. albicans biofilms. ALS1-5 were upregulated in all model systems, while ALS9 was mostly downregulated. ALS6 and HWP1 were overexpressed in all models except in the RHE and MTP, respectively. The expression levels of SAP1 were more pronounced in both in vitro models, while those of SAP2, SAP4 and SAP6 were higher in the in vivo model. Furthermore, SAP5 was highly upregulated in the in vivo and RHE models. For SAP9 and SAP10 similar gene expression levels were observed in all model systems. PLB genes were not considerably upregulated in biofilms, while LIP1-3, LIP5-7 and LIP9-10 were highly overexpressed in both in vitro models. Furthermore, an elevated lipase activity was detected in supernatans of biofilms grown in the MTP and RHE model. Conclusions Our findings show that HWP1 and most of the genes belonging to the ALS, SAP and LIP gene families are upregulated in C. albicans biofilms. Comparison of the fold expression between the various model systems revealed similar expression levels for some genes, while for others model-dependent expression

  4. Real-time augmented face

    OpenAIRE

    Lepetit, V.; Vacchetti, L; Thalmann, D; Fua, P.

    2003-01-01

    This real-time augmented reality demonstration relies on our tracking algorithm described in V. Lepetit et al (2003). This algorithm considers natural feature points, and then does not require engineering of the environment. It merges the information from preceding frames in traditional recursive tracking fashion with that provided by a very limited number of reference frames. This combination results in a system that does not suffer from jitter and drift, and can deal with drastic changes. T...

  5. Selection of reference genes for normalization of real-time PCR data in minipig heart failure model and evaluation of TNF-α mRNA expression.

    Science.gov (United States)

    Martino, Alessandro; Cabiati, Manuela; Campan, Manuela; Prescimone, Tommaso; Minocci, Daiana; Caselli, Chiara; Rossi, Anna Maria; Giannessi, Daniela; Del Ry, Silvia

    2011-05-20

    Real-time PCR is the benchmark method for measuring mRNA expression levels, but the accuracy and reproducibility of its data greatly depend on appropriate normalization strategies. Though the minipig model is largely used to study cardiovascular disease, no specific reference genes have been identified in porcine myocardium. The aim of the study was to identify and validate reference gene to be used in RT-PCR studies of failing (HF) and non-failing pig hearts. Eight candidate reference genes (GAPDH, ACTB, B2M, TBP, HPRT-1, PPIA, TOP2B, YWHAZ) were selected to compare cardiac tissue of normal (n=4) and HF (n=5) minipigs. The most stable genes resulted: HPRT-1, TBP, PPIA (right and left atrium); PPIA, GAPDH, ACTB (right ventricle); HPRT-1, TBP, GAPDH (left ventricle). The normalization strategy was tested analyzing mRNA expression of TNF-α, which is known to be up-regulated in HF and whose variations resulted more significant when normalized with the appropriately selected reference genes. The findings obtained in this study underline the importance to provide a set of reference genes to normalize mRNA expression in HF and control minipigs. The use of unvalidated reference genes can generate biased results because also their expression could be altered by the experimental conditions. Copyright © 2011 Elsevier B.V. All rights reserved.

  6. An eigenvalue approach for the automatic scaling of unknowns in model-based reconstructions: Application to real-time phase-contrast flow MRI.

    Science.gov (United States)

    Tan, Zhengguo; Hohage, Thorsten; Kalentev, Oleksandr; Joseph, Arun A; Wang, Xiaoqing; Voit, Dirk; Merboldt, K Dietmar; Frahm, Jens

    2017-12-01

    The purpose of this work is to develop an automatic method for the scaling of unknowns in model-based nonlinear inverse reconstructions and to evaluate its application to real-time phase-contrast (RT-PC) flow magnetic resonance imaging (MRI). Model-based MRI reconstructions of parametric maps which describe a physical or physiological function require the solution of a nonlinear inverse problem, because the list of unknowns in the extended MRI signal equation comprises multiple functional parameters and all coil sensitivity profiles. Iterative solutions therefore rely on an appropriate scaling of unknowns to numerically balance partial derivatives and regularization terms. The scaling of unknowns emerges as a self-adjoint and positive-definite matrix which is expressible by its maximal eigenvalue and solved by power iterations. The proposed method is applied to RT-PC flow MRI based on highly undersampled acquisitions. Experimental validations include numerical phantoms providing ground truth and a wide range of human studies in the ascending aorta, carotid arteries, deep veins during muscular exercise and cerebrospinal fluid during deep respiration. For RT-PC flow MRI, model-based reconstructions with automatic scaling not only offer velocity maps with high spatiotemporal acuity and much reduced phase noise, but also ensure fast convergence as well as accurate and precise velocities for all conditions tested, i.e. for different velocity ranges, vessel sizes and the simultaneous presence of signals with velocity aliasing. In summary, the proposed automatic scaling of unknowns in model-based MRI reconstructions yields quantitatively reliable velocities for RT-PC flow MRI in various experimental scenarios. Copyright © 2017 John Wiley & Sons, Ltd.

  7. The 1887 earthquake and tsunami in the Ligurian Sea: analysis of coastal effects studied by numerical modeling and prototype for real-time computing

    Science.gov (United States)

    Monnier, Angélique; Gailler, Audrey; Loevenbruck, Anne; Heinrich, Philippe; Hébert, Hélène

    2017-04-01

    The February 1887 earthquake in Italy (Imperia) triggered a tsunami well observed on the French and Italian coastlines. Tsunami waves were recorded on a tide gauge in the Genoa harbour with a small, recently reappraised maximum amplitude of about 10-12 cm (crest-to-trough). The magnitude of the earthquake is still debated in the recent literature, and discussed according to available macroseismic, tectonic and tsunami data. While the tsunami waveform observed in the Genoa harbour may be well explained with a magnitude smaller than 6.5 (Hébert et al., EGU 2015), we investigate in this study whether such source models are consistent with the tsunami effects reported elsewhere along the coastline. The idea is to take the opportunity of the fine bathymetric data recently synthetized for the French Tsunami Warning Center (CENALT) to test the 1887 source parameters using refined, nested grid tsunami numerical modeling down to the harbour scale. Several source parameters are investigated to provide a series of models accounting for various magnitudes and mechanisms. This allows us to compute the tsunami effects for several coastal sites in France (Nice, Villefranche, Antibes, Mandelieu, Cannes) and to compare with observations. Meanwhile we also check the computing time of the chosen scenarios to study whether running nested grids simulation in real time can be suitable in operational context in term of computational cost for these Ligurian scenarios. This work is supported by the FP7 ASTARTE project (Assessment Strategy and Risk Reduction for Tsunamis in Europe, grant 603839 FP7) and by the French PIA TANDEM (Tsunamis in the Atlantic and English ChaNnel: Definition of the Effects through Modeling) project (grant ANR-11-RSNR-00023).

  8. Overview of the Brooklyn traffic real-time ambient pollutant penetration and environmental dispersion (B-TRAPPED) study: theoretical background and model for design of field experiments.

    Science.gov (United States)

    Hahn, Intaek; Wiener, Russell W; Richmond-Bryant, Jennifer; Brixey, Laurie A; Henkle, Stacy W

    2009-12-01

    The Brooklyn traffic real-time ambient pollutant penetration and environmental dispersion (B-TRAPPED) study was a multidisciplinary field research project that investigated the transport, dispersion, and infiltration processes of traffic emission particulate matter (PM) pollutants in a near-highway urban residential area. The urban PM transport, dispersion, and infiltration processes were described mathematically in a theoretical model that was constructed to develop the experimental objectives of the B-TRAPPED study. In the study, simultaneous and continuous time-series PM concentration and meteorological data collected at multiple outdoor and indoor monitoring locations were used to characterize both temporal and spatial patterns of the PM concentration movements within microscale distances (dispersion of PM; (3) studying the influence of meteorological variables on the transport, dispersion, and infiltration processes; (4) characterizing the relationships between the building parameters and the infiltration mechanisms; (5) establishing a cause-and-effect relationship between outdoor-released PM and indoor PM concentrations and identifying the dominant mechanisms involved in the infiltration process; (6) evaluating the effectiveness of a shelter-in-place area for protection against outdoor-released PM pollutants; and (7) understanding the predominant airflow and pollutant dispersion patterns within the neighborhood using wind tunnel and CFD simulations. The 10 papers in this first set of papers presenting the results from the B-TRAPPED study address these objectives. This paper describes the theoretical background and models representing the interrelated processes of transport, dispersion, and infiltration. The theoretical solution for the relationship between the time-dependent indoor PM concentration and the initial PM concentration at the outdoor source was obtained. The theoretical models and solutions helped us to identify important parameters in the

  9. Real-Time PCR Quantification of Heteroplasmy in a Mouse Model with Mitochondrial DNA of C57BL/6 and NZB/BINJ Strains

    Science.gov (United States)

    Sangalli, Juliano Rodrigues; Rodrigues, Thiago Bittencourt; Smith, Lawrence Charles; Meirelles, Flávio Vieira; Chiaratti, Marcos Roberto

    2015-01-01

    Mouse models are widely employed to study mitochondrial inheritance, which have implications to several human diseases caused by mutations in the mitochondrial genome (mtDNA). These mouse models take advantage of polymorphisms between the mtDNA of the NZB/BINJ and the mtDNA of common inbred laboratory (i.e., C57BL/6) strains to generate mice with two mtDNA haplotypes (heteroplasmy). Based on PCR followed by restriction fragment length polymorphism (PCR-RFLP), these studies determine the level of heteroplasmy across generations and in different cell types aiming to understand the mechanisms underlying mitochondrial inheritance. However, PCR-RFLP is a time-consuming method of low sensitivity and accuracy that dependents on the use of restriction enzyme digestions. A more robust method to measure heteroplasmy has been provided by the use of real-time quantitative PCR (qPCR) based on allelic refractory mutation detection system (ARMS-qPCR). Herein, we report an ARMS-qPCR assay for quantification of heteroplasmy using heteroplasmic mice with mtDNA of NZB/BINJ and C57BL/6 origin. Heteroplasmy and mtDNA copy number were estimated in germline and somatic tissues, providing evidence of the reliability of the approach. Furthermore, it enabled single-step quantification of heteroplasmy, with sensitivity to detect as low as 0.1% of either NZB/BINJ or C57BL/6 mtDNA. These findings are relevant as the ARMS-qPCR assay reported here is fully compatible with similar heteroplasmic mouse models used to study mitochondrial inheritance in mammals. PMID:26274500

  10. Real-Time PCR Quantification of Heteroplasmy in a Mouse Model with Mitochondrial DNA of C57BL/6 and NZB/BINJ Strains.

    Directory of Open Access Journals (Sweden)

    Thiago Simões Machado

    Full Text Available Mouse models are widely employed to study mitochondrial inheritance, which have implications to several human diseases caused by mutations in the mitochondrial genome (mtDNA. These mouse models take advantage of polymorphisms between the mtDNA of the NZB/BINJ and the mtDNA of common inbred laboratory (i.e., C57BL/6 strains to generate mice with two mtDNA haplotypes (heteroplasmy. Based on PCR followed by restriction fragment length polymorphism (PCR-RFLP, these studies determine the level of heteroplasmy across generations and in different cell types aiming to understand the mechanisms underlying mitochondrial inheritance. However, PCR-RFLP is a time-consuming method of low sensitivity and accuracy that dependents on the use of restriction enzyme digestions. A more robust method to measure heteroplasmy has been provided by the use of real-time quantitative PCR (qPCR based on allelic refractory mutation detection system (ARMS-qPCR. Herein, we report an ARMS-qPCR assay for quantification of heteroplasmy using heteroplasmic mice with mtDNA of NZB/BINJ and C57BL/6 origin. Heteroplasmy and mtDNA copy number were estimated in germline and somatic tissues, providing evidence of the reliability of the approach. Furthermore, it enabled single-step quantification of heteroplasmy, with sensitivity to detect as low as 0.1% of either NZB/BINJ or C57BL/6 mtDNA. These findings are relevant as the ARMS-qPCR assay reported here is fully compatible with similar heteroplasmic mouse models used to study mitochondrial inheritance in mammals.

  11. Real time ray tracing of skeletal implicit surfaces

    DEFF Research Database (Denmark)

    Rouiller, Olivier; Bærentzen, Jakob Andreas

    Modeling and rendering in real time is usually done via rasterization of polygonal meshes. We present a method to model with skeletal implicit surfaces and an algorithm to ray trace these surfaces in real time in the GPU. Our skeletal representation of the surfaces allows to create smooth models...

  12. Identification of Suitable Reference Genes for Normalization of Real-Time Quantitative Polymerase Chain Reaction in an Intestinal Graft-Versus-Host Disease Mouse Model.

    Science.gov (United States)

    Li, X; Qiao, J; Yang, N; Mi, H; Chu, P; Xia, Y; Yao, H; Liu, Y; Qi, K; Yan, Z; Zeng, L; Xu, K

    2015-01-01

    With the development of real-time quantitative polymerase chain reaction (RT-qPCR) and intensive research on acute graft-versus-host disease (GVHD), selecting the best reference gene for normalization of RT-qPCR analysis in a GVHD model becomes more and more important. In this study, we aimed to identify suitable reference genes for mRNA studies in an intestinal GVHD mouse model after bone marrow transplantation (BMT). BALB/c recipients received 7.5 Gy total body irradiation (TBI) followed by injection of 5 × 10(6) bone marrow cells, without infusion of spleen cells for BMT, with infusion of 5 × 10(5) or 2.5 × 10(6) spleen cells for mild or moderate GVHD, respectively. Healthy mice were chosen as normal control subjects. Duodenum, jejunum, ileum, colon, and small intestine were collected at days 7, 14, 21, and 28 after transplantation. Transcription levels of 9 candidate genes, B2M, SDHA, HPRT, ACTB, GAPDH, HMBS, TBP, YWHAZ, and RPLP0, in each tissue were measured with the use of RT-qPCR. Combined data from these tissues in each group were defined as all samples. The expression stability of these genes was analyzed with the use of Genorm, Normfinder, Bestkeeper, and ΔCt. Our results showed that in all samples, ACTB and HMBS displayed the highest and lowest expression levels, respectively. Genorm identified HRPT and SDHA as the most stable reference genes, whereas Normfinder and ΔCt method showed HPRT as the most stably expressed gene. Bestkeeper ranked YWHAZ and HPRT as the top 2 most suitable genes. In conclusion, HPRT was recommended as the most suitable reference gene after comprehensive ranking, suggesting that it could be used as an internal control for mRNA studies in intestinal GVHD after BMT. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. A tissue-based approach to selection of reference genes for quantitative real-time PCR in a sheep osteoporosis model.

    Science.gov (United States)

    Schulze, Felix; Malhan, Deeksha; El Khassawna, Thaqif; Heiss, Christian; Seckinger, Anja; Hose, Dirk; Rösen-Wolff, Angela

    2017-12-19

    In order to better understand the multifactorial nature of osteoporosis, animal models are utilized and compared to healthy controls. Female sheep are well established as a model for osteoporosis induced by ovariectomy, calcium and vitamin D low diet, application of steroids, or a combination of these treatments. Transcriptional studies can be performed by applying quantitative real time PCR (RT-qPCR). RT-qPCR estimates mRNA-levels of target genes in relation to reference genes. A chosen set of reference genes should not show variation under experimental conditions. Currently, no standard reference genes are accepted for all tissue types and experimental conditions. Studies examining reference genes for sheep are rare and only one study described stable reference in mandibular bone. However, this type of bone differs from trabecular bone where most osteoporotic fractures occur. The present study aimed at identifying a set of reference genes for relative quantification of transcriptional activity of ovine spine bone and ovine in vitro differentiated mesenchymal stromal cells (MSC) for reliable comparability. Twelve candidate reference genes belonging to different functional classes were selected and their expression was measured from cultured ovMSCs (n = 18) and ovine bone samples (n = 16), respectively. RefFinder was used to rank the candidate genes. We identified B2M, GAPDH, RPL19 and YWHAZ as the best combination of reference genes for normalization of RT-qPCR results for transcriptional analyses of these ovine samples. This study demonstrates the importance of applying a set of reference genes for RT-qPCR analysis in sheep. Based on our data we recommend using four identified reference genes for relative quantification of gene expression studies in ovine bone or for in vitro experiments with osteogenically differentiated ovine MSCs.

  14. Real-time pulmonary graphics.

    Science.gov (United States)

    Mammel, Mark C; Donn, Steven M

    2015-06-01

    Real-time pulmonary graphics now enable clinicians to view lung mechanics and patient-ventilator interactions on a breath-to-breath basis. Displays of pressure, volume, and flow waveforms, pressure-volume and flow-volume loops, and trend screens enable clinicians to customize ventilator settings based on the underlying pathophysiology and responses of the individual patient. This article reviews the basic concepts of pulmonary graphics and demonstrates how they contribute to our understanding of respiratory physiology and the management of neonatal respiratory failure. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Real Time Plasma State Monitoring

    OpenAIRE

    Kudlacek, Ondrej

    2016-01-01

    The thesis describes several methods of plasma state monitoring for feedback control. For a tokamak device operation, one needs to gain in real time some information about the plasma state. The amount of needed information increases with the size of the device. In small machines, such as ISTTOK and Golem, the plasma current centroid position control is sufficient, as the heat fluxes are low and the plasma is in limiter regime. In larger devices, like RFX-mod, TCV or ASDEX-Upgrade with more co...

  16. Robust synthesis for real-time systems

    DEFF Research Database (Denmark)

    Larsen, Kim Guldstrand; Legay, Axel; Traonouez, Louis-Marie

    2014-01-01

    specification to an implementation, we need to reason about the possibility to effectively implement the theoretical specifications on physical systems, despite their limited precision. In the literature, this implementation problem has been linked to the robustness problem that analyzes the consequences......Specification theories for real-time systems allow reasoning about interfaces and their implementation models, using a set of operators that includes satisfaction, refinement, logical and parallel composition. To make such theories applicable throughout the entire design process from an abstract...

  17. Real-time infrared thermography detection of magnetic nanoparticle hyperthermia in a murine model under a non-uniform field configuration.

    Science.gov (United States)

    Rodrigues, Harley F; Mello, Francyelli M; Branquinho, Luis C; Zufelato, Nicholas; Silveira-Lacerda, Elisângela P; Bakuzis, Andris F

    2013-12-01

    Magnetic nanoparticle hyperthermia consists of an increase of the temperature of magnetic nanoparticles (heat centres) due to the interaction of their magnetic moments with an alternating magnetic field. In vivo experiments using this method usually use a few fibre-optic thermometers inserted in the animal body to monitor the heat deposition. As a consequence, only a few points of the 3D temperature distribution can be monitored by this invasive procedure. It is the purpose of this work to show that non-invasive infrared thermography is able to detect, in real time, magnetic nanoparticle hyperthermia as well as monitor the harmful field-induced eddy currents in a murine model with a subcutaneous tumour. This surface temperature measurement method has the potential to give information about the intratumoral temperature. The non-invasive magnetic hyperthermia experiments were performed at 300 kHz in non-uniform field configuration conditions in healthy mice and murine tumour induced by sarcoma S180. A soft ferrite-based biocompatible magnetic colloid consisting of manganese-ferrite nanoparticles surface-coated with citric acid were used in the experiments, which were extensively characterised by several techniques (transmission electron microscopy (TEM), X-ray diffraction (XRD), vibrating sample magnetometer (VSM)). The amplitude of the alternating magnetic fields was obtained from measurements using an AC field probe at similar experimental conditions. The temperature measurements were obtained from an infrared thermal camera and a fibre-optic thermometer. Three-minute magnetic hyperthermia experiments revealed surface temperature increase as high as 11 °K in healthy and (5 °K in S180 tumour) animals when injecting subcutaneously 2 mg of magnetic nanoparticles (86 μL of magnetic fluid), in contrast to around 1.5 °K (for healthy) and 2.5 °K (for cancerous) animals in experiments without the colloid due to field-induced eddy currents at the animal

  18. Precision real-time evaluation of bowel perfusion: accuracy of confocal endomicroscopy assessment of stoma in a controlled hemorrhagic shock model.

    Science.gov (United States)

    Diana, Michele; Noll, Eric; Charles, Anne-Laure; Diemunsch, Pierre; Geny, Bernard; Liu, Yu-Yin; Marchegiani, Francesco; Schiraldi, Luigi; Agnus, Vincent; Lindner, Veronique; Swanström, Lee; Dallemagne, Bernard; Marescaux, Jacques

    2017-02-01

    Confocal laser endomicroscopy (CLE) can provide real-time evaluation of bowel perfusion. We aimed to evaluate CLE perfusion imaging in a hemorrhagic shock model. Five pigs were equipped to ensure hemodynamic monitoring. Three ileostomies per animal (total n = 15) were randomly created (T0). Blood was withdrawn targeting a mean arterial pressure of 40 mmHg (shock phase, T1), for 90 min. Infusion of Ringer's lactate was started and continued for 90 min (T2). At the different time points: (a) stomas' mucosa was scanned with CLE; (b) capillary lactates were measured on blood obtained by puncturing stomas' mucosa; and (c) full-thickness stomas' biopsies were sampled for histology, mitochondrial respiratory rate (V 0 = basal and V ADP = respiratory rate in excess of adenosine diphosphate), and levels of superoxide anion evaluation. Functional capillary density (FCD) was measured using ad hoc software. Confocal scanning provided consistent and specific imaging of bowel hypoperfusion at T1: vascular hyperpermeability (blurred and enlarged capillaries) and edema (enhanced visualization of the brush border due to increased intercellular spaces and fluorescein leakage). At the end of T2, there was an improved capillary flow. FCD-A index expressed statistically significant correlation with (1) stoma capillary lactates (p = 0.023); (2) systemic capillary lactates (p = 0.031); (3) inflammation pathology score (p = 0.048); (4) central venous pressure (p = 0.0043); and (5) pulmonary artery pressure (p = 0.01). Stoma capillary lactates (mmol/L) were significantly increased at T1 (8.81 ± 4.23; p stomas.

  19. Real-time analysis keratometer

    Science.gov (United States)

    Adachi, Iwao P. (Inventor); Adachi, Yoshifumi (Inventor); Frazer, Robert E. (Inventor)

    1987-01-01

    A computer assisted keratometer in which a fiducial line pattern reticle illuminated by CW or pulsed laser light is projected on a corneal surface through lenses, a prismoidal beamsplitter quarterwave plate, and objective optics. The reticle surface is curved as a conjugate of an ideal corneal curvature. The fiducial image reflected from the cornea undergoes a polarization shift through the quarterwave plate and beamsplitter whereby the projected and reflected beams are separated and directed orthogonally. The reflected beam fiducial pattern forms a moire pattern with a replica of the first recticle. This moire pattern contains transverse aberration due to differences in curvature between the cornea and the ideal corneal curvature. The moire pattern is analyzed in real time by computer which displays either the CW moire pattern or a pulsed mode analysis of the transverse aberration of the cornea under observation, in real time. With the eye focused on a plurality of fixation points in succession, a survey of the entire corneal topography is made and a contour map or three dimensional plot of the cornea can be made as a computer readout in addition to corneal radius and refractive power analysis.

  20. Three-Month Real-Time Dengue Forecast Models: An Early Warning System for Outbreak Alerts and Policy Decision Support in Singapore

    Science.gov (United States)

    Shi, Yuan; Liu, Xu; Kok, Suet-Yheng; Rajarethinam, Jayanthi; Liang, Shaohong; Yap, Grace; Chong, Chee-Seng; Lee, Kim-Sung; Tan, Sharon S.Y.; Chin, Christopher Kuan Yew; Lo, Andrew; Kong, Waiming; Ng, Lee Ching; Cook, Alex R.

    2015-01-01

    Background: With its tropical rainforest climate, rapid urbanization, and changing demography and ecology, Singapore experiences endemic dengue; the last large outbreak in 2013 culminated in 22,170 cases. In the absence of a vaccine on the market, vector control is the key approach for prevention. Objectives: We sought to forecast the evolution of dengue epidemics in Singapore to provide early warning of outbreaks and to facilitate the public health response to moderate an impending outbreak. Methods: We developed a set of statistical models using least absolute shrinkage and selection operator (LASSO) methods to forecast the weekly incidence of dengue notifications over a 3-month time horizon. This forecasting tool used a variety of data streams and was updated weekly, including recent case data, meteorological data, vector surveillance data, and population-based national statistics. The forecasting methodology was compared with alternative approaches that have been proposed to model dengue case data (seasonal autoregressive integrated moving average and step-down linear regression) by fielding them on the 2013 dengue epidemic, the largest on record in Singapore. Results: Operationally useful forecasts were obtained at a 3-month lag using the LASSO-derived models. Based on the mean average percentage error, the LASSO approach provided more accurate forecasts than the other methods we assessed. We demonstrate its utility in Singapore’s dengue control program by providing a forecast of the 2013 outbreak for advance preparation of outbreak response. Conclusions: Statistical models built using machine learning methods such as LASSO have the potential to markedly improve forecasting techniques for recurrent infectious disease outbreaks such as dengue. Citation: Shi Y, Liu X, Kok SY, Rajarethinam J, Liang S, Yap G, Chong CS, Lee KS, Tan SS, Chin CK, Lo A, Kong W, Ng LC, Cook AR. 2016. Three-month real-time dengue forecast models: an early warning system for outbreak

  1. Verifying real-time systems against scenario-based requirements

    DEFF Research Database (Denmark)

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

    2009-01-01

    subset of the LSC language. By equivalently translating an LSC chart into an observer TA and then non-intrusively composing this observer with the original system model, the problem of verifying a real-time system against a scenario-based requirement reduces to a classical real-time model checking...

  2. SU-E-I-28: Development of Graphic Patient Models for a Real-Time Skin Dose Tracking System (DTS) for Fluoroscopic Interventional Procedures.

    Science.gov (United States)

    Rana, V; Bednarek, D; Wu, J; Rudin, S

    2012-06-01

    To develop a library of graphic human models that closely match patients undergoing interventional fluoroscopic procedures in order to obtain an accurate estimate of their skin dose. A dose tracking system (DTS) has been developed that calculates the dose to the patient's skin in real time during fluoroscopic procedures based on a graphical simulation of the x-ray system and the patient. The calculation is performed using a lookup table containing values of mGy per mAs at a reference point and inverse-square correction using the distance from the source to individual points on the skin. For proper inverse-square correction, the external shape of the graphic should closely match that of the patient. We are in the process of developing a library of 3D human graphic models categorized as a function of basic body type, sex, height and weight. Two different open- source software applications are being used to develop graphic models with varying weights and heights, to 'morph' the shapes for body type and to 'pose' them for proper positioning on the table. The DTS software is being designed such that the most appropriate body graphic can be automatically selected based on input of several basic patient dimensional metrics. A series of male and female body graphic models have been developed which vary in weight and height. Matching pairs have been constructed with arms at the side and over the head to simulate the usual placement in cardiac procedures. The error in skin dose calculation due to inverse-square correction is expected to be below 5% if the graphic can match the position of the patient's skin surface within 1 cm. A library of categorized body shapes should allow close matching of the graphic to the patient shape allowing more accurate determination of skin dose with the DTS. Support for this work was provided in part by NIH grants R43FD0158401, R44FD0158402, R01EB002873 and R01EB008425, and by Toshiba Medical Systems Corporation. © 2012 American Association

  3. Reverse transcription quantitative real-time polymerase chain reaction reference genes in the spared nerve injury model of neuropathic pain: validation and literature search.

    Science.gov (United States)

    Piller, Nicolas; Decosterd, Isabelle; Suter, Marc R

    2013-07-10

    The reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is a widely used, highly sensitive laboratory technique to rapidly and easily detect, identify and quantify gene expression. Reliable RT-qPCR data necessitates accurate normalization with validated control genes (reference genes) whose expression is constant in all studied conditions. This stability has to be demonstrated.We performed a literature search for studies using quantitative or semi-quantitative PCR in the rat spared nerve injury (SNI) model of neuropathic pain to verify whether any reference genes had previously been validated. We then analyzed the stability over time of 7 commonly used reference genes in the nervous system - specifically in the spinal cord dorsal horn and the dorsal root ganglion (DRG). These were: Actin beta (Actb), Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal proteins 18S (18S), L13a (RPL13a) and L29 (RPL29), hypoxanthine phosphoribosyltransferase 1 (HPRT1) and hydroxymethylbilane synthase (HMBS). We compared the candidate genes and established a stability ranking using the geNorm algorithm. Finally, we assessed the number of reference genes necessary for accurate normalization in this neuropathic pain model. We found GAPDH, HMBS, Actb, HPRT1 and 18S cited as reference genes in literature on studies using the SNI model. Only HPRT1 and 18S had been once previously demonstrated as stable in RT-qPCR arrays. All the genes tested in this study, using the geNorm algorithm, presented gene stability values (M-value) acceptable enough for them to qualify as potential reference genes in both DRG and spinal cord. Using the coefficient of variation, 18S failed the 50% cut-off with a value of 61% in the DRG. The two most stable genes in the dorsal horn were RPL29 and RPL13a; in the DRG they were HPRT1 and Actb. Using a 0.15 cut-off for pairwise variations we found that any pair of stable reference gene was sufficient for the normalization process

  4. Real Time Radiation Monitoring Using Nanotechnology

    Science.gov (United States)

    Li, Jing (Inventor); Wilkins, Richard T. (Inventor); Hanratty, James J. (Inventor); Lu, Yijiang (Inventor)

    2016-01-01

    System and method for monitoring receipt and estimating flux value, in real time, of incident radiation, using two or more nanostructures (NSs) and associated terminals to provide closed electrical paths and to measure one or more electrical property change values .DELTA.EPV, associated with irradiated NSs, during a sequence of irradiation time intervals. Effects of irradiation, without healing and with healing, of the NSs, are separately modeled for first order and second order healing. Change values.DELTA.EPV are related to flux, to cumulative dose received by NSs, and to radiation and healing effectivity parameters and/or.mu., associated with the NS material and to the flux. Flux and/or dose are estimated in real time, based on EPV change values, using measured .DELTA.EPV values. Threshold dose for specified changes of biological origin (usually undesired) can be estimated. Effects of time-dependent radiation flux are analyzed in pre-healing and healing regimes.

  5. Real-time Interactive Tree Animation.

    Science.gov (United States)

    Quigley, Ed; Yu, Yue; Huang, Jingwei; Lin, Winnie; Fedkiw, Ronald

    2017-01-30

    We present a novel method for posing and animating botanical tree models interactively in real time. Unlike other state of the art methods which tend to produce trees that are overly flexible, bending and deforming as if they were underwater plants, our approach allows for arbitrarily high stiffness while still maintaining real-time frame rates without spurious artifacts, even on quite large trees with over ten thousand branches. This is accomplished by using an articulated rigid body model with as-stiff-as-desired rotational springs in conjunction with our newly proposed simulation technique, which is motivated both by position based dynamics and the typical O(N) algorithms for articulated rigid bodies. The efficiency of our algorithm allows us to pose and animate trees with millions of branches or alternatively simulate a small forest comprised of many highly detailed trees. Even using only a single CPU core, we can simulate ten thousand branches in real time while still maintaining quite crisp user interactivity. This has allowed us to incorporate our framework into a commodity game engine to run interactively even on a low-budget tablet. We show that our method is amenable to the incorporation of a large variety of desirable effects such as wind, leaves, fictitious forces, collisions, fracture, etc.

  6. Formalizing Real-Time Embedded System into Promela

    Directory of Open Access Journals (Sweden)

    Sukvanich Punwess

    2015-01-01

    Full Text Available We propose an alternative of formalization of the real-time embedded system into Promela model. The proposed formal model supports the essential features of the real-time embedded system, including system resource-constrained handling, task prioritization, task synchronization, real-time preemption, the parallelism of resources via DMA. Meanwhile, the model is also fully compatible with the partial order reduction algorithm for model checking. The timed automata of the real-time embedded system are considered and transformed into Promela, in our approach, by replacing time ticking into the repeated cycle of the timed values to do the conditional guard to enable the synchronization among the whole system operations. Our modeling approach could satisfactorily verify a small real-time system with parameterized dependent tasks and different scheduling topologies.

  7. LEMming: A Linear Error Model to Normalize Parallel Quantitative Real-Time PCR (qPCR Data as an Alternative to Reference Gene Based Methods.

    Directory of Open Access Journals (Sweden)

    Ronny Feuer

    Full Text Available Gene expression analysis is an essential part of biological and medical investigations. Quantitative real-time PCR (qPCR is characterized with excellent sensitivity, dynamic range, reproducibility and is still regarded to be the gold standard for quantifying transcripts abundance. Parallelization of qPCR such as by microfluidic Taqman Fluidigm Biomark Platform enables evaluation of multiple transcripts in samples treated under various conditions. Despite advanced technologies, correct evaluation of the measurements remains challenging. Most widely used methods for evaluating or calculating gene expression data include geNorm and ΔΔCt, respectively. They rely on one or several stable reference genes (RGs for normalization, thus potentially causing biased results. We therefore applied multivariable regression with a tailored error model to overcome the necessity of stable RGs.We developed a RG independent data normalization approach based on a tailored linear error model for parallel qPCR data, called LEMming. It uses the assumption that the mean Ct values within samples of similarly treated groups are equal. Performance of LEMming was evaluated in three data sets with different stability patterns of RGs and compared to the results of geNorm normalization. Data set 1 showed that both methods gave similar results if stable RGs are available. Data set 2 included RGs which are stable according to geNorm criteria, but became differentially expressed in normalized data evaluated by a t-test. geNorm-normalized data showed an effect of a shifted mean per gene per condition whereas LEMming-normalized data did not. Comparing the decrease of standard deviation from raw data to geNorm and to LEMming, the latter was superior. In data set 3 according to geNorm calculated average expression stability and pairwise variation, stable RGs were available, but t-tests of raw data contradicted this. Normalization with RGs resulted in distorted data contradicting

  8. LEMming: A Linear Error Model to Normalize Parallel Quantitative Real-Time PCR (qPCR) Data as an Alternative to Reference Gene Based Methods.

    Science.gov (United States)

    Feuer, Ronny; Vlaic, Sebastian; Arlt, Janine; Sawodny, Oliver; Dahmen, Uta; Zanger, Ulrich M; Thomas, Maria

    2015-01-01

    Gene expression analysis is an essential part of biological and medical investigations. Quantitative real-time PCR (qPCR) is characterized with excellent sensitivity, dynamic range, reproducibility and is still regarded to be the gold standard for quantifying transcripts abundance. Parallelization of qPCR such as by microfluidic Taqman Fluidigm Biomark Platform enables evaluation of multiple transcripts in samples treated under various conditions. Despite advanced technologies, correct evaluation of the measurements remains challenging. Most widely used methods for evaluating or calculating gene expression data include geNorm and ΔΔCt, respectively. They rely on one or several stable reference genes (RGs) for normalization, thus potentially causing biased results. We therefore applied multivariable regression with a tailored error model to overcome the necessity of stable RGs. We developed a RG independent data normalization approach based on a tailored linear error model for parallel qPCR data, called LEMming. It uses the assumption that the mean Ct values within samples of similarly treated groups are equal. Performance of LEMming was evaluated in three data sets with different stability patterns of RGs and compared to the results of geNorm normalization. Data set 1 showed that both methods gave similar results if stable RGs are available. Data set 2 included RGs which are stable according to geNorm criteria, but became differentially expressed in normalized data evaluated by a t-test. geNorm-normalized data showed an effect of a shifted mean per gene per condition whereas LEMming-normalized data did not. Comparing the decrease of standard deviation from raw data to geNorm and to LEMming, the latter was superior. In data set 3 according to geNorm calculated average expression stability and pairwise variation, stable RGs were available, but t-tests of raw data contradicted this. Normalization with RGs resulted in distorted data contradicting literature, while

  9. Autonomous Real Time Requirements Tracing

    Science.gov (United States)

    Plattsmier, George; Stetson, Howard

    2014-01-01

    One of the more challenging aspects of software development is the ability to verify and validate the functional software requirements dictated by the Software Requirements Specification (SRS) and the Software Detail Design (SDD). Insuring the software has achieved the intended requirements is the responsibility of the Software Quality team and the Software Test team. The utilization of Timeliner-TLX(sup TM) Auto- Procedures for relocating ground operations positions to ISS automated on-board operations has begun the transition that would be required for manned deep space missions with minimal crew requirements. This transition also moves the auto-procedures from the procedure realm into the flight software arena and as such the operational requirements and testing will be more structured and rigorous. The autoprocedures would be required to meet NASA software standards as specified in the Software Safety Standard (NASASTD- 8719), the Software Engineering Requirements (NPR 7150), the Software Assurance Standard (NASA-STD-8739) and also the Human Rating Requirements (NPR-8705). The Autonomous Fluid Transfer System (AFTS) test-bed utilizes the Timeliner-TLX(sup TM) Language for development of autonomous command and control software. The Timeliner-TLX(sup TM) system has the unique feature of providing the current line of the statement in execution during real-time execution of the software. The feature of execution line number internal reporting unlocks the capability of monitoring the execution autonomously by use of a companion Timeliner-TLX(sup TM) sequence as the line number reporting is embedded inside the Timeliner-TLX(sup TM) execution engine. This negates I/O processing of this type data as the line number status of executing sequences is built-in as a function reference. This paper will outline the design and capabilities of the AFTS Autonomous Requirements Tracker, which traces and logs SRS requirements as they are being met during real-time execution of the

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

    Science.gov (United States)

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

    2018-01-01

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

  11. Novel Method Probe-based Real-Time PCR to Detect 2 Single-Nucleotide Polymorphisms Close to Each Other: HFE Hemochromatosis Gene Model.

    Science.gov (United States)

    Malta, Frederico S V; Reis, Zilma N; Cabral, Antônio C V

    2016-10-01

    Hereditary hemochromatosis is known as the most common genetic disorder among individuals of European genetic background. It is possible to find 2 mutations closely placed in the HFE gene (H63D and S65C) and this proximity can cause errors when genotyped by real-time polymerase chain reaction (PCR) genotyping assay. The aim of this study was to develop a hydrolysis probe-based PCR assay for detection of the H63D and S65C mutations without interference from on each other. Herein the study involved the standardization of an improvement of the real-time PCR 5' nuclease assay to detect the desired mutations close placed using a same probe system. The assay analytical properties performances were tested, including the primers selectivity and detection limits. Also, the interexaminer reproducibility and repeatability of assay were estimated in 30 blood samples. Others 153 results of samples were compared with reference method (PCR_RFLP) and the accordance of the results evaluated by Fleiss' κ method. The results of variation of interexaminer reproducibility and repeatability of assay were not statistically relevant (Pmethods by Fleiss' κ analysis showed that 5' nuclease assay identified the H63D and S65C haplotype as well as the reference method in all 153 tested samples. Our results showed that novel method probe-based real-time PCR were capable to detect 2 adjacent polymorphisms without errors in genotyping.

  12. A kinetic-based sigmoidal model for the polymerase chain reaction and its application to high-capacity absolute quantitative real-time PCR

    Directory of Open Access Journals (Sweden)

    Stewart Don

    2008-05-01

    Full Text Available Abstract Background Based upon defining a common reference point, current real-time quantitative PCR technologies compare relative differences in amplification profile position. As such, absolute quantification requires construction of target-specific standard curves that are highly resource intensive and prone to introducing quantitative errors. Sigmoidal modeling using nonlinear regression has previously demonstrated that absolute quantification can be accomplished without standard curves; however, quantitative errors caused by distortions within the plateau phase have impeded effective implementation of this alternative approach. Results Recognition that amplification rate is linearly correlated to amplicon quantity led to the derivation of two sigmoid functions that allow target quantification via linear regression analysis. In addition to circumventing quantitative errors produced by plateau distortions, this approach allows the amplification efficiency within individual amplification reactions to be determined. Absolute quantification is accomplished by first converting individual fluorescence readings into target quantity expressed in fluorescence units, followed by conversion into the number of target molecules via optical calibration. Founded upon expressing reaction fluorescence in relation to amplicon DNA mass, a seminal element of this study was to implement optical calibration using lambda gDNA as a universal quantitative standard. Not only does this eliminate the need to prepare target-specific quantitative standards, it relegates establishment of quantitative scale to a single, highly defined entity. The quantitative competency of this approach was assessed by exploiting "limiting dilution assay" for absolute quantification, which provided an independent gold standard from which to verify quantitative accuracy. This yielded substantive corroborating evidence that absolute accuracies of ± 25% can be routinely achieved. Comparison

  13. Real-time scene generator

    Science.gov (United States)

    Lord, Eric; Shand, David J.; Cantle, Allan J.

    1996-05-01

    This paper describes the techniques which have been developed for an infra-red (IR) target, countermeasure and background image generation system working in real time for HWIL and Trial Proving applications. Operation is in the 3 to 5 and 8 to 14 micron bands. The system may be used to drive a scene projector (otherwise known as a thermal picture synthesizer) or for direct injection into equipment under test. The provision of realistic IR target and countermeasure trajectories and signatures, within representative backgrounds, enables the full performance envelope of a missile system to be evaluated. It also enables an operational weapon system to be proven in a trials environment without compromising safety. The most significant technique developed has been that of line by line synthesis. This minimizes the processing delays to the equivalent of 1.5 frames from input of target and sightline positions to the completion of an output image scan. Using this technique a scene generator has been produced for full closed loop HWIL performance analysis for the development of an air to air missile system. Performance of the synthesis system is as follows: 256 * 256 pixels per frame; 350 target polygons per frame; 100 Hz frame rate; and Gouraud shading, simple reflections, variable geometry targets and atmospheric scaling. A system using a similar technique has also bee used for direct insertion into the video path of a ground to air weapon system in live firing trials. This has provided realistic targets without degrading the closed loop performance. Delay of the modified video signal has been kept to less than 5 lines. The technique has been developed using a combination of 4 high speed Intel i860 RISC processors in parallel with the 4000 series XILINX field programmable gate arrays (FPGA). Start and end conditions for each line of target pixels are prepared and ordered in the I860. The merging with background pixels and output shading and scaling is then carried out in

  14. Mobile real time radiography system

    Energy Technology Data Exchange (ETDEWEB)

    Vigil, J.; Taggart, D.; Betts, S. [Los Alamos National Lab., NM (United States)] [and others

    1997-11-01

    A 450-keV Mobile Real Time Radiography (RTR) System was delivered to Los Alamos National Laboratory (LANL) in January 1996. It was purchased to inspect containers of radioactive waste produced at (LANL). Since its delivery it has been used to radiograph more than 600 drums of radioactive waste at various LANL sites. It has the capability of inspecting waste containers of various sizes from <1-gal. buckets up to standard waste boxes (SWB, dimensions 54.5 in. x 71 in. x 37 in.). It has three independent x-ray acquisition formats. The primary system used is a 12- in. image intensifier, the second is a 36-in. linear diode array (LDA) and the last is an open system. It is fully self contained with on board generator, HVAC, and a fire suppression system. It is on a 53-ft long x 8-ft. wide x 14-ft. high trailer that can be moved over any highway requiring only an easily obtainable overweight permit because it weights {approximately}38 tons. It was built to conform to industry standards for a cabinet system which does not require an exclusion zone. The fact that this unit is mobile has allowed us to operate where the waste is stored, rather than having to move the waste to a fixed facility.

  15. Adapting RealTime Physics

    Science.gov (United States)

    George, E. A.; Fleisch, D. A.; Voytas, P. A.; Dollhopf, W. E.

    2001-10-01

    We are changing the way we teach our introductory physics sequence, restructuring the laboratory portion of these courses around research-based curricular materials that make use of MBL and digital video capture techniques. As the first step in this project, we adapted RealTime Physics (RTP) Mechanics and Electric Circuits labs for an introductory Mechanics and an introductory E&M course. The RTP Mechanics labs had to be rather severely modified in order to fit the constraints of the Mechanics course (1.5 hours of lab a week). In both courses, we have also created several new experiments that make use of MBL and video tools and use an approach similar to that of the RTP experiments. We will briefly describe these new experiments, and discuss how well the modified RTP and new experiments have worked in the context of our curriculum. In addition, we will report pre- and post-instruction results on standard conceptual exams. We also retested about half the students in the E&M course nine months after they had completed the course in order to see how well they retained the concepts.

  16. Hard Real-Time Networking on FIrewire

    NARCIS (Netherlands)

    Zhang, Yuchen; Orlic, B.; Visser, P.M.; Broenink, Johannes F.; Marquet, P; McGuire, N; Wurmsdobler, P

    2005-01-01

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

  17. A real-time Global Warming Index.

    Science.gov (United States)

    Haustein, K; Allen, M R; Forster, P M; Otto, F E L; Mitchell, D M; Matthews, H D; Frame, D J

    2017-11-13

    We propose a simple real-time index of global human-induced warming and assess its robustness to uncertainties in climate forcing and short-term climate fluctuations. This index provides improved scientific context for temperature stabilisation targets and has the potential to decrease the volatility of climate policy. We quantify uncertainties arising from temperature observations, climate radiative forcings, internal variability and the model response. Our index and the associated rate of human-induced warming is compatible with a range of other more sophisticated methods to estimate the human contribution to observed global temperature change.

  18. Students Collecting Real time Data

    Science.gov (United States)

    Miller, P.

    2006-05-01

    Students Collecting Real-Time Data The Hawaiian Islands Humpback Whale National Marine Sanctuary has created opportunities for middle and high school students to become Student Researchers and to be involved in real-time marine data collection. It is important that we expose students to different fields of science and encourage them to enter scientific fields of study. The Humpback Whale Sanctuary has an education visitor center in Kihei, Maui. Located right on the beach, the site has become a living classroom facility. There is a traditional Hawaiian fishpond fronting the property. The fishpond wall is being restored, using traditional methods. The site has the incredible opportunity of incorporating Hawaiian cultural practices with scientific studies. The Sanctuary offers opportunities for students to get involved in monitoring and data collection studies. Invasive Seaweed Study: Students are collecting data on invasive seaweed for the University of Hawaii. They pull a large net through the shallow waters. Seaweed is sorted, identified and weighed. The invasive seaweeds are removed. The data is recorded and sent to UH. Remote controlled monitoring boats: The sanctuary has 6 boogie board sized remote controlled boats used to monitor reefs. Boats have a camera with lights on the underside. The boats have water quality monitoring devices and GPS units. The video from the underwater camera is transmitted via a wireless transmission. Students are able to monitor the fish, limu and invertebrate populations on the reef and collect water quality data via television monitors or computers. The boat can also pull a small plankton tow net. Data is being compiled into data bases. Artificial Reef Modules: The Sanctuary has a scientific permit from the state to build and deploy artificial reef modules. High school students are designing and building modules. These are deployed out in the Fishpond fronting the Sanctuary site and students are monitoring them on a weekly basis

  19. Real-time embedded systems design principles and engineering practices

    CERN Document Server

    Fan, Xiaocong

    2015-01-01

    This book integrates new ideas and topics from real time systems, embedded systems, and software engineering to give a complete picture of the whole process of developing software for real-time embedded applications. You will not only gain a thorough understanding of concepts related to microprocessors, interrupts, and system boot process, appreciating the importance of real-time modeling and scheduling, but you will also learn software engineering practices such as model documentation, model analysis, design patterns, and standard conformance. This book is split into four parts to help you

  20. Real Time Simulation of Power Grid Disruptions

    Energy Technology Data Exchange (ETDEWEB)

    Chinthavali, Supriya [ORNL; Dimitrovski, Aleksandar D [ORNL; Fernandez, Steven J [ORNL; Groer, Christopher S [ORNL; Nutaro, James J [ORNL; Olama, Mohammed M [ORNL; Omitaomu, Olufemi A [ORNL; Shankar, Mallikarjun [ORNL; Spafford, Kyle L [ORNL; Vacaliuc, Bogdan [ORNL

    2012-11-01

    DOE-OE and DOE-SC workshops (Reference 1-3) identified the key power grid problem that requires insight addressable by the next generation of exascale computing is coupling of real-time data streams (1-2 TB per hour) as the streams are ingested to dynamic models. These models would then identify predicted disruptions in time (2-4 seconds) to trigger the smart grid s self healing functions. This project attempted to establish the feasibility of this approach and defined the scientific issues, and demonstrated example solutions to important smart grid simulation problems. These objectives were accomplished by 1) using the existing frequency recorders on the national grid to establish a representative and scalable real-time data stream; 2) invoking ORNL signature identification algorithms; 3) modeling dynamically a representative region of the Eastern interconnect using an institutional cluster, measuring the scalability and computational benchmarks for a national capability; and 4) constructing a prototype simulation for the system s concept of smart grid deployment. The delivered ORNL enduring capability included: 1) data processing and simulation metrics to design a national capability justifying exascale applications; 2) Software and intellectual property built around the example solutions; 3) demonstrated dynamic models to design few second self-healing.

  1. Real-Time MENTAT programming language and architecture

    Science.gov (United States)

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

    1989-01-01

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

  2. Models of complex attitude systems

    DEFF Research Database (Denmark)

    Sørensen, Bjarne Taulo

    production systems was modelled. The analysis was based on data from a cross-cultural survey involving 1931 participants from Belgium, Denmark, Germany and Poland. The survey questionnaire contained measures of personal value orientations and attitudes towards environment and nature, industrial food...

  3. Games and Scenarios for Real-Time System Validation

    DEFF Research Database (Denmark)

    Li, Shuhao

    This thesis presents research on the validation of real-time embedded software systems in the context of model-based development. The thesis proposes scenario-based and game-theoretic approaches to system analysis, verification, synthesis and testing to address the challenges that arise from...... communicating real-time systems can be modeled and specified with LSC. By translating LSC to timed automata (TAs), we reduce scenario-based model consistency checking and property verification to CTL real-time model checking problems, and reduce scenario-based synthesis to a timed game solving problem....... By linking our prototype translators with existing model checker Uppaal and game solver Uppaal-Tiga, we show that these methods contribute to the interaction correctness and timeliness of early system designs. The thesis also shows that testing a real-time reactive system can be viewed as playing a timed...

  4. Real-time simulation of hand motion for prosthesis control.

    Science.gov (United States)

    Blana, Dimitra; Chadwick, Edward K; van den Bogert, Antonie J; Murray, Wendy M

    2017-04-01

    Individuals with hand amputation suffer substantial loss of independence. Performance of sophisticated prostheses is limited by the ability to control them. To achieve natural and simultaneous control of all wrist and hand motions, we propose to use real-time biomechanical simulation to map between residual EMG and motions of the intact hand. Here we describe a musculoskeletal model of the hand using only extrinsic muscles to determine whether real-time performance is possible. Simulation is 1.3 times faster than real time, but the model is locally unstable. Methods are discussed to increase stability and make this approach suitable for prosthesis control.

  5. Space Shuttle Main Engine real time stability analysis

    Science.gov (United States)

    Kuo, F. Y.

    1993-01-01

    The Space Shuttle Main Engine (SSME) is a reusable, high performance, liquid rocket engine with variable thrust. The engine control system continuously monitors the engine parameters and issues propellant valve control signals in accordance with the thrust and mixture ratio commands. A real time engine simulation lab was installed at MSFC to verify flight software and to perform engine dynamic analysis. A real time engine model was developed on the AD100 computer system. This model provides sufficient fidelity on the dynamics of major engine components and yet simplified enough to be executed in real time. The hardware-in-the-loop type simulation and analysis becomes necessary as NASA is continuously improving the SSME technology, some with significant changes in the dynamics of the engine. The many issues of interfaces between new components and the engine can be better understood and be resolved prior to the firing of the engine. In this paper, the SSME real time simulation Lab at the MSFC, the SSME real time model, SSME engine and control system stability analysis, both in real time and non-real time is presented.

  6. Dual-EKF-Based Real-Time Celestial Navigation for Lunar Rover

    Directory of Open Access Journals (Sweden)

    Li Xie

    2012-01-01

    Full Text Available A key requirement of lunar rover autonomous navigation is to acquire state information accurately in real-time during its motion and set up a gradual parameter-based nonlinear kinematics model for the rover. In this paper, we propose a dual-extended-Kalman-filter- (dual-EKF- based real-time celestial navigation (RCN method. The proposed method considers the rover position and velocity on the lunar surface as the system parameters and establishes a constant velocity (CV model. In addition, the attitude quaternion is considered as the system state, and the quaternion differential equation is established as the state equation, which incorporates the output of angular rate gyroscope. Therefore, the measurement equation can be established with sun direction vector from the sun sensor and speed observation from the speedometer. The gyro continuous output ensures the algorithm real-time operation. Finally, we use the dual-EKF method to solve the system equations. Simulation results show that the proposed method can acquire the rover position and heading information in real time and greatly improve the navigation accuracy. Our method overcomes the disadvantage of the cumulative error in inertial navigation.

  7. Model documentation for relations between continuous real-time and discrete water-quality constituents in the North Fork Ninnescah River upstream from Cheney Reservoir, south-central Kansas, 1999--2009

    Science.gov (United States)

    Stone, Mandy L.; Graham, Jennifer L.; Gatotho, Jackline W.

    2013-01-01

    Cheney Reservoir in south-central Kansas is one of the primary sources of water for the city of Wichita. The North Fork Ninnescah River is the largest contributing tributary to Cheney Reservoir. The U.S. Geological Survey has operated a continuous real-time water-quality monitoring station since 1998 on the North Fork Ninnescah River. Continuously measured water-quality physical properties include streamflow, specific conductance, pH, water temperature, dissolved oxygen, and turbidity. Discrete water-quality samples were collected during 1999 through 2009 and analyzed for sediment, nutrients, bacteria, and other water-quality constituents. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physical properties to estimate concentrations of those constituents of interest that are not easily measured in real time because of limitations in sensor technology and fiscal constraints. Regression models were published in 2006 that were based on a different dataset collected during 1997 through 2003. This report updates those models using discrete and continuous data collected during January 1999 through December 2009. Models also were developed for five new constituents, including additional nutrient species and indicator bacteria. The water-quality information in this report is important to the city of Wichita because it allows the concentrations of many potential pollutants of interest, including nutrients and sediment, to be estimated in real time and characterized over conditions and time scales that would not be possible otherwise.

  8. Real-time Pricing in Power Markets

    DEFF Research Database (Denmark)

    Boom, Anette; Schwenen, Sebastian

    We examine welfare eects of real-time pricing in electricity markets. Before stochastic energy demand is known, competitive retailers contract with nal consumers who exogenously do not have real-time meters. After demand is realized, two electricity generators compete in a uniform price auction t....... In the Bertrand case, welfare is the same with all or no consumers on smart meters.......We examine welfare eects of real-time pricing in electricity markets. Before stochastic energy demand is known, competitive retailers contract with nal consumers who exogenously do not have real-time meters. After demand is realized, two electricity generators compete in a uniform price auction...... to satisfy demand from retailers acting on behalf of subscribed customers and from consumers with real-time meters. Increasing the number of consumers on real-time pricing does not always increase welfare since risk-averse consumers dislike uncertain and high prices arising through market power...

  9. Towards Real-Time GOMS.

    Science.gov (United States)

    John, Bonnie E.; And Others

    This report presents an analysis of an expert performing a highly interactive computer task. The analysis uses GOMS models, specifying the Goals, Operators, Methods, and Selection rules used by the expert; the GOMS models are implemented within a unified theory of cognition called Soar. Two models are presented, one with function-level operators,…

  10. Reviewing real-time performance of nuclear reactor safety systems

    Energy Technology Data Exchange (ETDEWEB)

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

    1993-08-01

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

  11. A Real time network at home

    OpenAIRE

    Hanssen, F.T.Y.; Jansen, P.G.; Hartel, Pieter H.; Scholten, Johan; Vervoort, Wiek; Karelse, F.

    2001-01-01

    This paper proposes a home network which integrates both real-time and non-real-time capabilities for one coherent, distributed architecture. Such a network is not yet available. Our network will support inexpensive, small appliances as well as more expensive, large appliances. The network is based on a new type of real-time token protocol that uses scheduling to achieve optimal token-routing through the network. Depending on the scheduling algorithm, bandwidth utilisations of 100 percent are...

  12. Modular specification of real-time systems

    DEFF Research Databa