Real-Time Spatio-Temporal Query Processing in Mobile Ad-Hoc Sensor Networks

Personal communication devices are increasingly equipped with sensors that are able to collect and locally store information from their environs. The mobility of users carrying such devices, and hence the mobility of sensor readings in space and time, opens new horizons for interesting applications. In particular, we envision a system in which the collective sensing, storage and communication resources, and mobility of these devices could be leveraged to query the state of (possibly remote) neighborhoods. Such queries would have spatio-temporal constraints which must be met for the query answers to be useful. Using a simplified mobility model, we analytically quantify the benefits from cooperation (in terms of the system's ability to satisfy spatio-temporal constraints), which we show to go beyond simple space-time tradeoffs. In managing the limited storage resources of such cooperative systems, the goal should be to minimize the number of unsatisfiable spatio-temporal constraints. We show that Data Centric Storage (DCS), or "directed placement", is a viable approach for achieving this goal, but only when the underlying network is well connected. Alternatively, we propose, "amorphous placement", in which sensory samples are cached locally, and shuffling of cached samples is used to diffuse the sensory data throughout the whole network. We evaluate conditions under which directed versus amorphous placement strategies would be more efficient. These results lead us to propose a hybrid placement strategy, in which the spatio-temporal constraints associated with a sensory data type determine the most appropriate placement strategy for that data type. We perform an extensive simulation study to evaluate the performance of directed, amorphous, and hybrid placement protocols when applied to queries that are subject to timing constraints. Our results show that, directed placement is better for queries with moderately tight deadlines, whereas amorphous placement is better for queries with looser deadlines, and that under most operational conditions, the hybrid technique gives the best compromise.

Context-aware real-time assistant architecture for pervasive healthcare

The aging population in many countries brings into focus rising healthcare costs and pressure on conventional healthcare services. Pervasive healthcare has emerged as a viable solution capable of providing a technology-driven approach to alleviate such problems by allowing healthcare to move from the hospital-centred care to self-care, mobile care, and at-home care. The state-of-the-art studies in this field, however, lack a systematic approach for providing comprehensive pervasive healthcare solutions from data collection to data interpretation and from data analysis to data delivery. In this thesis we introduce a Context-aware Real-time Assistant (CARA) architecture that integrates novel approaches with state-of-the-art technology solutions to provide a full-scale pervasive healthcare solution with the emphasis on context awareness to help maintaining the well-being of elderly people. CARA collects information about and around the individual in a home environment, and enables accurately recognition and continuously monitoring activities of daily living. It employs an innovative reasoning engine to provide accurate real-time interpretation of the context and current situation assessment. Being mindful of the use of the system for sensitive personal applications, CARA includes several mechanisms to make the sophisticated intelligent components as transparent and accountable as possible, it also includes a novel cloud-based component for more effective data analysis. To deliver the automated real-time services, CARA supports interactive video and medical sensor based remote consultation. Our proposal has been validated in three application domains that are rich in pervasive contexts and real-time scenarios: (i) Mobile-based Activity Recognition, (ii) Intelligent Healthcare Decision Support Systems and (iii) Home-based Remote Monitoring Systems.

Real time analysis of atmospheric single particles in urban environments using aerosol time of flight mass spectrometry

In order to determine the size-resolved chemical composition of single particles in real-time an ATOFMS was deployed at urban background sites in Paris and Barcelona during the MEGAPOLI and SAPUSS monitoring campaigns respectively. The particle types detected during MEGAPOLI included several carbonaceous species, metal-containing types and sea-salt. Elemental carbon particle types were highly abundant, with 86% due to fossil fuel combustion and 14% attributed to biomass burning. Furthermore, 79% of the EC was apportioned to local emissions and 21% to continental transport. The carbonaceous particle types were compared with quantitative measurements from other instruments, and while direct correlations using particle counts were poor, scaling of the ATOFMS counts greatly improved the relationship. During SAPUSS carbonaceous species, sea-salt, dust, vegetative debris and various metal-containing particle types were identified. Throughout the campaign the site was influenced by air masses altering the composition of particles detected. During North African air masses the city was heavily influenced by Saharan dust. A regional stagnation was also observed leading to a large increase in carbonaceous particle counts. While the ATOFMS provides a list of particle types present during the measurement campaigns, the data presented is not directly quantitative. The quantitative response of the ATOFMS to metals was examined by comparing the ion signals within particle mass spectra and to hourly mass concentrations of; Na, K, Ca, Ti, V, Cr, Mn, Fe, Zn and Pb. The ATOFMS was found to have varying correlations with these metals depending on sampling issues such as matrix effects. The strongest correlations were observed for Al, Fe, Zn, Mn and Pb. Overall the results of this work highlight the excellent ability of the ATOFMS in providing composition and mixing state information on atmospheric particles at high time resolution. However they also show its limitations in delivering quantitative information directly.

Real-time decision aid display

Gemstone Team Future Firefighting Advancements

Temporal representation of state transitions

This paper describes a knowledge-based temporal representation of state transitions for industrial real-time systems. To allow expression of uncertainty, we shall define fluents as disjuncts of positive/negative time-varying properties. A state of the world is represented as a collection of fluents, which is usually incomplete in the sense that neither the positive form nor the negative form of some properties can be implied from it. The world under consideration is assumed to persist in a given state until an action(s) takes place to effect a transition of it into another state, where actions may either be instantaneous or durative. High-level causal laws are characterized in terms of relationships between actions and the involved world states. An effect completion axiom is imposed on each causal law to guarantee that all the fluents that can be affected by the performance of the corresponding action are governed. This completion requirement is practical for most industrial real-time applications and in fact provides a simple and effective treatment to the so-called frame problem.

Synthesis and enzymatic evaluation of the guanosine analogue 2-amino-6-mercapto-7-methylpurine ribonucleoside (MESG): insights into the phosphorolysis reaction mechanism based on the blueprint transition state: SN1 or SN2?

A modified experimental procedure for the synthesis of MESG (2-amino-6-mercapto-7-methylpurine ribonucleoside) 1 has been successfully performed and its full characterization is presented. High resolution ESI(+)-MSMS indicates both the nucleoside bond cleavage as the main fragmentation in the gas phase and a possible SN1 mechanism. Ab initio transition state calculations based on the blue print transition state support this mechanistic rationale and discard an alternative SN2 mechanism. Assays using purine nucleoside phosphorylase (PNP) enzyme (human and M. tuberculosis sources) indicate its efficiency in the phosphorolysis of MESG and allow the quantitative determination of inorganic phosphate in real time assay.

Two-wire thermocouples: A nonlinear state estimation approach to temperature reconstruction.

The problem of measuring high frequency variations in temperature is described, and the need for some form of reconstruction introduced. One method of reconstructing temperature measurements is to use the signals from two thermocouples of differing diameter. Two existing methods for processing such measurements and reconstructing the higher frequency components are described. These are compared to a novel reconstruction algorithm based on a nonlinear extended Kalman filter. The performance of this filter is found to compare favorably, in a number of ways, with the existing techniques, and it is suggested that such a technique would be viable for the online reconstruction of temperatures in real time.

Stability and dynamical behavior in a lake-model and implications for regime shifts in real lakes

A modified abstract version of the Comprehensive Aquatic Simulation Model (CASM) is found to exhibit three types of folded bifurcations due to nutrient loading. The resulting bifurcation diagrams account for nonlinear dynamics such as regime shifts and cyclic changes between clear-water state and turbid state that have actually been observed in real lakes. In particular, pulse-perturbation simulations based on the model presented suggest that temporal behaviors of real lakes after biomanipulations can be explained by pulse-dynamics in complex ecosystems, and that not only the amplitude (manipulated abundance of organisms) but also the phase (timing) is important for restoring lakes by biomanipulation. Ecosystem management in terms of possible irreversible changes in ecosystems induced by regime shifts is also discussed. (c) 2007 Elsevier B.V All rights reserved.

A Low Complexity Real-time MIMO-Preprocessing For Fixed Complexity Sphere Decoder

Modern Multiple-Input Multiple-Output (MIMO) communication systems place huge demands on embedded processing resources in terms of throughput, latency and resource utilization. State-of-the-art MIMO detector algorithms, such as Fixed-Complexity Sphere Decoding (FSD), rely on efficient channel preprocessing involving numerous calculations of the pseudo-inverse of the channel matrix by QR Decomposition (QRD) and ordering. These highly complicated operations can quickly become the critical prerequisite for real-time MIMO detection, exaggerated as the number of antennas in a MIMO detector increases. This paper describes a sorted QR decomposition (SQRD) algorithm extended for FSD, which significantly reduces the complexity and latency
of this preprocessing step and increases the throughput of MIMO detection. It merges the calculations of the QRD and ordering operations to avoid multiple iterations of QRD. Specifically, it shows that SQRD reduces the computational complexity by over 60-70% when compared to conventional
MIMO preprocessing algorithms. In 4x4 to 7x7 MIMO cases, the approach suffers merely 0.16-0.2 dB reduction in Bit Error Rate (BER) performance.

Pyroelectric and piezoelectric scanning microscopy applied to reveal the bipolar state of 4-iodo-4 '-nitrobiphenyl (INBP)

Two recent scanning probe techniques were applied to investigate the bipolar twin state of 4-iodo-4'-nitrobiphenyl (INBP) crystals. Solution grown crystals of INBP show typically a morphology which does not express that of a mono-domain polar structure (Fdd2, mm2). From previous X-ray diffraction a twinning volume ratio of similar to 70 : 30 is now explained by two unipolar domains (Flack parameter: 0.075(29)) of opposite orientation of the molecular dipoles, joined by a transition zone showing a width of similar to 140 mm. Scanning pyroelectric microscopy (SPEM) demonstrates a continuous transition of the polarization P from +P into -P across the zone. Application of piezoelectric force microscopy (PFM) confirms unipolar alignment of INBP molecules down to a resolution of similar to 20 nm. A previously proposed real structure for INBP crystals built from lamellae with antiparallel alignment is thus rejected. Anomalous X-ray scattering was used to determine the absolute molecular orientation in the two domains. End faces of the polar axis 2 are thus made up by NO2 groups. Using a previously determined negative pyroelectric coefficient pc leads to a confirmation also by a SPEM analysis. Calculated values for functional group interactions (D...A), (A...A), (D...D) and the stochastic theory of polarity formation allow us to predict that NO2 groups should terminate corresponding faces. Following the present analysis, INBP may represent a first example undergoing dipole reversal upon growth to end up in a bipolar state.

NanoStreams: Advancing the Hardware and Software Stack for Real-Time Analytics on Fast Data Streams

NanoStreams is a consortium project funded by the European Commission under its FP7 programme and is a major effort to address the challenges of processing vast amounts of data in real-time, with a markedly lower carbon footprint than the state of the art. The project addresses both the energy challenge and the high-performance required by emerging applications in real-time streaming data analytics. NanoStreams achieves this goal by designing and building disruptive micro-server solutions incorporating real-silicon prototype micro-servers based on System-on-Chip and reconfigurable hardware technologies.

Conductivity sensor technology application in steady state migration test

In this paper the current development of the steady state migration test was reviewed. Experiments were carried out for a series of concrete mixes with the steady state migration test in which conductivity sensor technology is applied. With the developed steady state migration test, conductivity in anolyte, loop current and temperature can be monitored in real time. The experimental results are conductive to understand the mechanism of chloride migration during both unsteady state and steady state. The conductivity of anolyte could be used to calculate the chloride concentration in anolyte and the theoretical correlation between them was explained. Over all, the developed steady state migration is an effective, convenient, well-defined in theory and plentiful with information method which could be used to determine the chloride diffusion coefficient of cementitious materials.

High Performance Real-time Pre-Processing for Fixed-Complexity Sphere Decoder

Pre-processing (PP) of received symbol vector and channel matrices is an essential pre-requisite operation for Sphere Decoder (SD)-based detection of Multiple-Input Multiple-Output (MIMO) wireless systems. PP is a highly complex operation, but relative to the total SD workload it represents a relatively small fraction of the overall computational cost of detecting an OFDM MIMO frame in standards such as 802.11n. Despite this, real-time PP architectures are highly inefficient, dominating the resource cost of real-time SD architectures. This paper resolves this issue. By reorganising the ordering and QR decomposition sub operations of PP, we describe a Field Programmable Gate Array (FPGA)-based PP architecture for the Fixed Complexity Sphere Decoder (FSD) applied to 4 × 4 802.11n MIMO which reduces resource cost by 50% as compared to state-of-the-art solutions whilst maintaining real-time performance.

Algorithms and architectures for real-time control

Algorithm and Architectures for Real-Time Control Workshop had the objective to investigate the state of the art and to present new research and application results in software and hardware for real-timecontrol, as well as to bring together engeneers and computer scientists who are researchers, developers and practitioners, both from the academic and the industrial world.

BIMP: A real-time biological model of multi-scale keypoint detection in V1

We present an improved, biologically inspired and multiscale keypoint operator. Models of single- and double-stopped hypercomplex cells in area V1 of the mammalian visual cortex are used to detect stable points of high complexity at multiple scales. Keypoints represent line and edge crossings, junctions and terminations at fine scales, and blobs at coarse scales. They are detected by applying first and second derivatives to responses of complex cells in combination with two inhibition schemes to suppress responses along lines and edges. A number of optimisations make our new algorithm much faster than previous biologically inspired models, achieving real-time performance on modern GPUs and competitive speeds on CPUs. In this paper we show that the keypoints exhibit state-of-the-art repeatability in standardised benchmarks, often yielding best-in-class performance. This makes them interesting both in biological models and as a useful detector in practice. We also show that keypoints can be used as a data selection step, significantly reducing the complexity in state-of-the-art object categorisation. (C) 2014 Elsevier B.V. All rights reserved.