Real-Time software control of neural stimulation in a closed loop Animat system

A recent area for investigation into the development of adaptable robot control is the use of living neuronal networks to control a mobile robot. The so-called Animat paradigm comprises a neuronal network (the ‘brain’) connected to an external embodiment (in this case a mobile robot), facilitating potentially robust, adaptable robot control and increased understanding of neural processes. Sensory input from the robot is provided to the neuronal network via stimulation on a number of electrodes embedded in a specialist Petri dish (Multi Electrode Array (MEA)); accurate control of this stimulation is vital. We present software tools allowing precise, near real-time control of electrical stimulation on MEAs, with fast switching between electrodes and the application of custom stimulus waveforms. These Linux-based tools are compatible with the widely used MEABench data acquisition system. Benefits include rapid stimulus modulation in response to neuronal activity (closed loop) and batch processing of stimulation protocols.

Real-time context-aware network security policy enforcement system (RC-NSPES)

The major technical objectives of the RC-NSPES are to provide a framework for the concurrent operation of reactive and pro-active security functions to deliver efficient and optimised intrusion detection schemes as well as enhanced and highly correlated rule sets for more effective alerts management and root-cause analysis. The design and implementation of the RC-NSPES solution includes a number of innovative features in terms of real-time programmable embedded hardware (FPGA) deployment as well as in the integrated management station. These have been devised so as to deliver enhanced detection of attacks and contextualised alerts against threats that can arise from both the network layer and the application layer protocols. The resulting architecture represents an efficient and effective framework for the future deployment of network security systems.

Experimental characterization of nonlinear systems: a real-time evaluation of the analogous Chua`s circuit behavior

This paper presents an experimental characterization of the behavior of an analogous version of the Chua`s circuit. The electronic circuit signals are captured using a data acquisition board (DAQ) and processed using LabVIEW environment. The following aspects of the time series analysis are analyzed: time waveforms, phase portraits, frequency spectra, Poincar, sections, and bifurcation diagram. The circuit behavior is experimentally mapped with the parameter variations, where are identified equilibrium points, periodic and chaotic attractors, and bifurcations. These analysis techniques are performed in real-time and can be applied to characterize, with precision, several nonlinear systems.

Adaptive, Decentralized, And Real-Time Sampling Strategies For Resource Constrained Hydraulic And Hydrologic Sensor Networks

We discuss the development and performance of a low-power sensor node (hardware, software and algorithms) that autonomously controls the sampling interval of a suite of sensors based on local state estimates and future predictions of water flow. The problem is motivated by the need to accurately reconstruct abrupt state changes in urban watersheds and stormwater systems. Presently, the detection of these events is limited by the temporal resolution of sensor data. It is often infeasible, however, to increase measurement frequency due to energy and sampling constraints. This is particularly true for real-time water quality measurements, where sampling frequency is limited by reagent availability, sensor power consumption, and, in the case of automated samplers, the number of available sample containers. These constraints pose a significant barrier to the ubiquitous and cost effective instrumentation of large hydraulic and hydrologic systems. Each of our sensor nodes is equipped with a low-power microcontroller and a wireless module to take advantage of urban cellular coverage. The node persistently updates a local, embedded model of flow conditions while IP-connectivity permits each node to continually query public weather servers for hourly precipitation forecasts. The sampling frequency is then adjusted to increase the likelihood of capturing abrupt changes in a sensor signal, such as the rise in the hydrograph – an event that is often difficult to capture through traditional sampling techniques. Our architecture forms an embedded processing chain, leveraging local computational resources to assess uncertainty by analyzing data as it is collected. A network is presently being deployed in an urban watershed in Michigan and initial results indicate that the system accurately reconstructs signals of interest while significantly reducing energy consumption and the use of sampling resources. We also expand our analysis by discussing the role of this approach for the efficient real-time measurement of stormwater systems.

Real-Time Flood Forecasting Systems In Flanders

As a highly urbanized and flood prone region, Flanders has experienced multiple floods causing significant damage in the past. In response to the floods of 1998 and 2002 the Flemish Environment Agency, responsible for managing 1 400 km of unnavigable rivers, started setting up a real time flood forecasting system in 2003. Currently the system covers almost 2 000 km of unnavigable rivers, for which flood forecasts are accessible online (www.waterinfo.be). The forecasting system comprises more than 1 000 hydrologic and 50 hydrodynamic models which are supplied with radar rainfall, rainfall forecasts and on-site observations. Forecasts for the next 2 days are generated hourly, while 10 day forecasts are generated twice a day. Additionally, twice daily simulations based on percentile rainfall forecasts (from EPS predictions) result in uncertainty bands for the latter. Subsequent flood forecasts use the most recent rainfall predictions and observed parameters at any time while uncertainty on the longer-term is taken into account. The flood forecasting system produces high resolution dynamic flood maps and graphs at about 200 river gauges and more than 3 000 forecast points. A customized emergency response system generates phone calls and text messages to a team of hydrologists initiating a pro-active response to prevent upcoming flood damage. The flood forecasting system of the Flemish Environment Agency is constantly evolving and has proven to be an indispensable tool in flood crisis management. This was clearly the case during the November 2010 floods, when the agency issued a press release 2 days in advance allowing water managers, emergency services and civilians to take measures.

Optimized scheduling in real-time environments with column generation

Im Bereich sicherheitsrelevanter eingebetteter Systeme stellt sich der Designprozess von Anwendungen als sehr komplex dar. Entsprechend einer gegebenen Hardwarearchitektur lassen sich Steuergeräte aufrüsten, um alle bestehenden Prozesse und Signale pünktlich auszuführen. Die zeitlichen Anforderungen sind strikt und müssen in jeder periodischen Wiederkehr der Prozesse erfüllt sein, da die Sicherstellung der parallelen Ausführung von größter Bedeutung ist. Existierende Ansätze können schnell Designalternativen berechnen, aber sie gewährleisten nicht, dass die Kosten für die nötigen Hardwareänderungen minimal sind. Wir stellen einen Ansatz vor, der kostenminimale Lösungen für das Problem berechnet, die alle zeitlichen Bedingungen erfüllen. Unser Algorithmus verwendet Lineare Programmierung mit Spaltengenerierung, eingebettet in eine Baumstruktur, um untere und obere Schranken während des Optimierungsprozesses bereitzustellen. Die komplexen Randbedingungen zur Gewährleistung der periodischen Ausführung verlagern sich durch eine Zerlegung des Hauptproblems in unabhängige Unterprobleme, die als ganzzahlige lineare Programme formuliert sind. Sowohl die Analysen zur Prozessausführung als auch die Methoden zur Signalübertragung werden untersucht und linearisierte Darstellungen angegeben. Des Weiteren präsentieren wir eine neue Formulierung für die Ausführung mit fixierten Prioritäten, die zusätzlich Prozessantwortzeiten im schlimmsten anzunehmenden Fall berechnet, welche für Szenarien nötig sind, in denen zeitliche Bedingungen an Teilmengen von Prozessen und Signalen gegeben sind. Wir weisen die Anwendbarkeit unserer Methoden durch die Analyse von Instanzen nach, welche Prozessstrukturen aus realen Anwendungen enthalten. Unsere Ergebnisse zeigen, dass untere Schranken schnell berechnet werden können, um die Optimalität von heuristischen Lösungen zu beweisen. Wenn wir optimale Lösungen mit Antwortzeiten liefern, stellt sich unsere neue Formulierung in der Laufzeitanalyse vorteilhaft gegenüber anderen Ansätzen dar. Die besten Resultate werden mit einem hybriden Ansatz erzielt, der heuristische Startlösungen, eine Vorverarbeitung und eine heuristische mit einer kurzen nachfolgenden exakten Berechnungsphase verbindet.

A real-time video quality estimator for emerging wireless multimedia systems

Wireless Mesh Networks (WMNs) are increasingly deployed to enable thousands of users to share, create, and access live video streaming with different characteristics and content, such as video surveillance and football matches. In this context, there is a need for new mechanisms for assessing the quality level of videos because operators are seeking to control their delivery process and optimize their network resources, while increasing the user’s satisfaction. However, the development of in-service and non-intrusive Quality of Experience assessment schemes for real-time Internet videos with different complexity and motion levels, Group of Picture lengths, and characteristics, remains a significant challenge. To address this issue, this article proposes a non-intrusive parametric real-time video quality estimator, called MultiQoE that correlates wireless networks’ impairments, videos’ characteristics, and users’ perception into a predicted Mean Opinion Score. An instance of MultiQoE was implemented in WMNs and performance evaluation results demonstrate the efficiency and accuracy of MultiQoE in predicting the user’s perception of live video streaming services when compared to subjective, objective, and well-known parametric solutions.

Real-time simulation of large open quantum spin systems driven by dissipation

We consider a large quantum system with spins 12 whose dynamics is driven entirely by measurements of the total spin of spin pairs. This gives rise to a dissipative coupling to the environment. When one averages over the measurement results, the corresponding real-time path integral does not suffer from a sign problem. Using an efficient cluster algorithm, we study the real-time evolution from an initial antiferromagnetic state of the two-dimensional Heisenberg model, which is driven to a disordered phase, not by a Hamiltonian, but by sporadic measurements or by continuous Lindblad evolution.

Real-time dynamics of open quantum spin systems driven by dissipative processes

We study the real-time evolution of large open quantum spin systems in two spatial dimensions, whose dynamics is entirely driven by a dissipative coupling to the environment. We consider different dissipative processes and investigate the real-time evolution from an ordered phase of the Heisenberg or XY model towards a disordered phase at late times, disregarding unitary Hamiltonian dynamics. The corresponding Kossakowski-Lindblad equation is solved via an efficient cluster algorithm. We find that the symmetry of the dissipative process determines the time scales, which govern the approach towards a new equilibrium phase at late times. Most notably, we find a slow equilibration if the dissipative process conserves any of the magnetization Fourier modes. In these cases, the dynamics can be interpreted as a diffusion process of the conserved quantity.

Real-time simulation of nonequilibrium transport of magnetization in large open quantum spin systems driven by dissipation

Using quantum Monte Carlo, we study the nonequilibrium transport of magnetization in large open strongly correlated quantum spin-12 systems driven by purely dissipative processes that conserve the uniform or staggered magnetization, disregarding unitary Hamiltonian dynamics. We prepare both a low-temperature Heisenberg ferromagnet and an antiferromagnet in two parts of the system that are initially isolated from each other. We then bring the two subsystems in contact and study their real-time dissipative dynamics for different geometries. The flow of the uniform or staggered magnetization from one part of the system to the other is described by a diffusion equation that can be derived analytically.

Real time passenger information systems and quality of bus services

One of the main problems in urban areas is the steady growth in car ownership and traffic levels. Therefore, the challenge of sustainability is focused on a shift of the demand for mobility from cars to collective means of transport. For this end, buses are a key element of the public transport systems. In this respect Real Time Passenger Information (RTPI) systems help citizens change their travel behaviour towards more sustainable transport modes. This paper provides an assessment methodology which evaluates how RTPI systems improve the quality of bus services in two European cities, Madrid and Bremerhaven. In the case of Madrid, bus punctuality has increased by 3%. Regarding the travellers perception, Madrid raised its quality of service by 6% while Bremerhaven increased by 13%. On the other hand, the users ́ perception of Public Transport (PT) image increased by 14%.

On real-time partitioned multicore systems

Partitioning is a common approach to developing mixed-criticality systems, where partitions are isolated from each other both in the temporal and the spatial domain in order to prevent low-criticality subsystems from compromising other subsystems with high level of criticality in case of misbehaviour. The advent of many-core processors, on the other hand, opens the way to highly parallel systems in which all partitions can be allocated to dedicated processor cores. This trend will simplify processor scheduling, although other issues such as mutual interference in the temporal domain may arise as a consequence of memory and device sharing. The paper describes an architecture for multi-core partitioned systems including critical subsystems built with the Ada Ravenscar profile. Some implementation issues are discussed, and experience on implementing the ORK kernel on the XtratuM partitioning hypervisor is presented.

Quality of bus services performance: benefits of real time passenger information systems

One of the main problems in urban areas is the steady growth in car ownership and traffic levels. Therefore, the challenge of sustainability is focused on a shift of the demand for mobility from cars to collective means of transport. For this purpose, buses are a key element of the public transport systems. In this respect Real Time Passenger Information (RTPI) systems help people change their travel behaviour towards more sustainable transport modes. This paper provides an assessment methodology which evaluates how RTPI systems improve the quality of bus services performance in two European cities, Madrid and Bremerhaven. In the case of Madrid, bus punctuality has increased by 3%. Regarding the travellers perception, Madrid raised its quality of service by 6% while Bremerhaven increased by 13%. On the other hand, the users¿ perception of Public Transport (PT) image increased by 14%.

A Dynamically Adaptable Image Processing Application Trading Off Between High Performance, Consumption and Dependability in Real Time

As embedded systems evolve, problems inherent to technology become important limitations. In less than ten years, chips will exceed the maximum allowed power consumption affecting performance, since, even though the resources available per chip are increasing, frequency of operation has stalled. Besides, as the level of integration is increased, it is difficult to keep defect density under control, so new fault tolerant techniques are required. In this demo work, a new dynamically adaptable virtual architecture (ARTICo3) to allow dynamic and context-aware use of resources is implemented in a high performance Wireless Sensor node (HiReCookie) to perform an image processing application.

Real-time 3D semi-local surface patch extraction using GPGPU

Feature vectors can be anything from simple surface normals to more complex feature descriptors. Feature extraction is important to solve various computer vision problems: e.g. registration, object recognition and scene understanding. Most of these techniques cannot be computed online due to their complexity and the context where they are applied. Therefore, computing these features in real-time for many points in the scene is impossible. In this work, a hardware-based implementation of 3D feature extraction and 3D object recognition is proposed to accelerate these methods and therefore the entire pipeline of RGBD based computer vision systems where such features are typically used. The use of a GPU as a general purpose processor can achieve considerable speed-ups compared with a CPU implementation. In this work, advantageous results are obtained using the GPU to accelerate the computation of a 3D descriptor based on the calculation of 3D semi-local surface patches of partial views. This allows descriptor computation at several points of a scene in real-time. Benefits of the accelerated descriptor have been demonstrated in object recognition tasks. Source code will be made publicly available as contribution to the Open Source Point Cloud Library.