Situation assessment through multi-modal sensing of dynamic environments to support cognitive robot control

Awareness of emerging situations in a dynamic operational environment of a robotic assistive device is an essential capability of such a cognitive system, based on its effective and efficient assessment of the prevailing situation. This allows the system to interact with the environment in a sensible (semi)autonomous / pro-active manner without the need for frequent interventions from a supervisor. In this paper, we report a novel generic Situation Assessment Architecture for robotic systems directly assisting humans as developed in the CORBYS project. This paper presents the overall architecture for situation assessment and its application in proof-of-concept Demonstrators as developed and validated within the CORBYS project. These include a robotic human follower and a mobile gait rehabilitation robotic system. We present an overview of the structure and functionality of the Situation Assessment Architecture for robotic systems with results and observations as collected from initial validation on the two CORBYS Demonstrators.

Multi-modal fingerprinting for multimedia assets: optimisation of media security protection in online distribution environments

Since the advent of the internet in every day life in the 1990s, the barriers to producing, distributing and consuming multimedia data such as videos, music, ebooks, etc. have steadily been lowered for most computer users so that almost everyone with internet access can join the online communities who both produce, consume and of course also share media artefacts. Along with this trend, the violation of personal data privacy and copyright has increased with illegal file sharing being rampant across many online communities particularly for certain music genres and amongst the younger age groups. This has had a devastating effect on the traditional media distribution market; in most cases leaving the distribution companies and the content owner with huge financial losses. To prove that a copyright violation has occurred one can deploy fingerprinting mechanisms to uniquely identify the property. However this is currently based on only uni-modal approaches. In this paper we describe some of the design challenges and architectural approaches to multi-modal fingerprinting currently being examined for evaluation studies within a PhD research programme on optimisation of multi-modal fingerprinting architectures. Accordingly we outline the available modalities that are being integrated through this research programme which aims to establish the optimal architecture for multi-modal media security protection over the internet as the online distribution environment for both legal and illegal distribution of media products.

Multi-level Input Fusion in multi-modal systems

Context-aware multimodal interactive systems aim to adapt to the needs and behavioural patterns of users and offer a way forward for enhancing the efficacy and quality of experience (QoE) in human-computer interaction. The various modalities that constribute to such systems each provide a specific uni-modal response that is integratively presented as a multi-modal interface capable of interpretation of multi-modal user input and appropriately responding to it through dynamically adapted multi-modal interactive flow management , This paper presents an initial background study in the context of the first phase of a PhD research programme in the area of optimisation of data fusion techniques to serve multimodal interactivite systems, their applications and requirements.

A framework towards multi-modal fingerprinting scheme for multimedia assets

Fingerprinting is a well known approach for identifying multimedia data without having the original data present but what amounts to its essence or ”DNA”. Current approaches show insufficient deployment of three types of knowledge that could be brought to bear in providing a finger printing framework that remains effective, efficient and can accommodate both the whole as well as elemental protection at appropriate levels of abstraction to suit various Foci of Interest (FoI) in an image or cross media artefact. Thus our proposed framework aims to deliver selective composite fingerprinting that remains responsive to the requirements for protection of whole or parts of an image which may be of particularly interest and be especially vulnerable to attempts at rights violation. This is powerfully aided by leveraging both multi-modal information as well as a rich spectrum of collateral context knowledge including both image-level collaterals as well as the inevitably needed market intelligence knowledge such as customers’ social networks interests profiling which we can deploy as a crucial component of our Fingerprinting Collateral Knowledge. This is used in selecting the special FoIs within an image or other media content that have to be selectively and collaterally protected.

A framework towards a multi-modal fingerprinting scheme for multimedia assets

Fingerprinting is a well known approach for identifying multimedia data without having the original data present but instead what amounts to its essence or 'DNA'. Current approaches show insufficient deployment of various types of knowledge that could be brought to bear in providing a fingerprinting framework that remains effective, efficient and can accommodate both the whole as well as elemental protection at appropriate levels of abstraction to suit various Zones of Interest (ZoI) in an image or cross media artefact. The proposed framework aims to deliver selective composite fingerprinting that is powerfully aided by leveraging both multi-modal information as well as a rich spectrum of collateral context knowledge including both image-level collaterals and also the inevitably needed market intelligence knowledge such as customers' social networks interests profiling which we can deploy as a crucial component of our fingerprinting collateral knowledge.

Robust control system design for generalized state-space systems

Robustness in multi-variable control system design requires that the solution to the design problem be insensitive to perturbations in the system data. In this paper we discuss measures of robustness for generalized state-space, or descriptor, systems and describe algorithmic techniques for optimizing robustness for various applications.

In-street wind direction variability in the vicinity of a busy intersection in central London

We present results from fast-response wind measurements within and above a busy intersection between two street canyons (Marylebone Road and Gloucester Place) in Westminster, London taken as part of the DAPPLE (Dispersion of Air Pollution and Penetration into the Local Environment; www.dapple.org.uk) 2007 field campaign. The data reported here were collected using ultrasonic anemometers on the roof-top of a building adjacent to the intersection and at two heights on a pair of lamp-posts on opposite sides of the intersection. Site characteristics, data analysis and the variation of intersection flow with the above-roof wind direction (θref) are discussed. Evidence of both flow channelling and recirculation was identified within the canyon, only a few metres from the intersection for along-street and across-street roof-top winds respectively. Results also indicate that for oblique rooftop flows, the intersection flow is a complex combination of bifurcated channelled flows, recirculation and corner vortices. Asymmetries in local building geometry around the intersection and small changes in the background wind direction (changes in 15-min mean θref of 5–10 degrees) were also observed to have profound influences on the behaviour of intersection flow patterns. Consequently, short time-scale variability in the background flow direction can lead to highly scattered in-street mean flow angles masking the true multi-modal features of the flow and thus further complicating modelling challenges.

Stray light analysis of SALEX instrument

Discrepancies between recent global earth albedo anomaly data obtained from the climate models, space and ground observations call for a new and better earth reflectance measurement technique. The SALEX (Space Ashen Light Explorer) instrument is a space-based visible and IR instrument for precise estimation of the global earth albedo by measuring the ashen light reflected off the shadowy side of the Moon from the low earth orbit. The instrument consists of a conventional 2-mirror telescope, a pair of a 3-mirror visible imager and an IR bolometer. The performance of this unique multi-channel optical system is sensitive to the stray light contamination due to the complex optical train incorporating several reflecting and refracting elements, associated mounts and the payload mechanical enclosure. This could be further aggravated by the very bright and extended observation target (i.e. the Moon). In this paper, we report the details of extensive stray light analysis including ghosts and cross-talks, leading to the optimum set of stray light precautions for the highest signal-to-noise ratio attainable.

Robust real-time tracking for visual surveillance

This paper describes a real-time multi-camera surveillance system that can be applied to a range of application domains. This integrated system is designed to observe crowded scenes and has mechanisms to improve tracking of objects that are in close proximity. The four component modules described in this paper are (i) motion detection using a layered background model, (ii) object tracking based on local appearance, (iii) hierarchical object recognition, and (iv) fused multisensor object tracking using multiple features and geometric constraints. This integrated approach to complex scene tracking is validated against a number of representative real-world scenarios to show that robust, real-time analysis can be performed. Copyright (C) 2007 Hindawi Publishing Corporation. All rights reserved.

Motion estimation through approximated densities

Many techniques are currently used for motion estimation. In the block-based approaches the most common procedure applied is the block-matching based on various algorithms. To refine the motion estimates resulting from the full search or any coarse search algorithm, one can find few applications of Kalman filtering, mainly in the intraframe scheme. The Kalman filtering technique applicability for block-based motion estimation is rather limited due to discontinuities in the dynamic behaviour of the motion vectors. Therefore, we propose an application of the concept of the filtering by approximated densities (FAD). The FAD, originally introduced to alleviate limitations due to conventional Kalman modelling, is applied to interframe block-motion estimation. This application uses a simple form of FAD involving statistical characteristics of multi-modal distributions up to second order.

Development and application of a method for the purification of free shigatoxigenic bacteriophage from environmental samples

Shiga toxin producing Escherichia coli (STEC) strains are foodborne pathogens whose ability to produce Shiga toxin (Stx) is due to the integration of Stx-encoding lambdoid bacteriophage (Stx phage). Circulating, infective Stx phages are very difficult to isolate, purify and propagate such that there is no information on their genetic composition and properties. Here we describe a novel approach that exploits the phage's ability to infect their host and form a lysogen, thus enabling purification of Stx phages by a series of sequential lysogen isolation and induction steps. A total of 15 Stx phages were rigorously purified from water samples in this way, classified by TEM and genotyped using a PCR-based multi-loci characterisation system. Each phage possessed only one variant of each target gene type, thus confirming its purity, with 9 of the 15 phages possessing a short tail-spike gene and identified by TEM as Podoviridae. The remaining 6 phages possessed long tails, four of which appeared to be contractile in nature (Myoviridae) and two of which were morphologically very similar to bacteriophage lambda (Siphoviridae).

Realistic mean field forward predictions for the integration of co-registered EEG/fMRI

Brain activity can be measured non-invasively with functional imaging techniques. Each pixel in such an image represents a neural mass of about 105 to 107 neurons. Mean field models (MFMs) approximate their activity by averaging out neural variability while retaining salient underlying features, like neurotransmitter kinetics. However, MFMs incorporating the regional variability, realistic geometry and connectivity of cortex have so far appeared intractable. This lack of biological realism has led to a focus on gross temporal features of the EEG. We address these impediments and showcase a "proof of principle" forward prediction of co-registered EEG/fMRI for a full-size human cortex in a realistic head model with anatomical connectivity, see figure 1. MFMs usually assume homogeneous neural masses, isotropic long-range connectivity and simplistic signal expression to allow rapid computation with partial differential equations. But these approximations are insufficient in particular for the high spatial resolution obtained with fMRI, since different cortical areas vary in their architectonic and dynamical properties, have complex connectivity, and can contribute non-trivially to the measured signal. Our code instead supports the local variation of model parameters and freely chosen connectivity for many thousand triangulation nodes spanning a cortical surface extracted from structural MRI. This allows the introduction of realistic anatomical and physiological parameters for cortical areas and their connectivity, including both intra- and inter-area connections. Proper cortical folding and conduction through a realistic head model is then added to obtain accurate signal expression for a comparison to experimental data. To showcase the synergy of these computational developments, we predict simultaneously EEG and fMRI BOLD responses by adding an established model for neurovascular coupling and convolving "Balloon-Windkessel" hemodynamics. We also incorporate regional connectivity extracted from the CoCoMac database [1]. Importantly, these extensions can be easily adapted according to future insights and data. Furthermore, while our own simulation is based on one specific MFM [2], the computational framework is general and can be applied to models favored by the user. Finally, we provide a brief outlook on improving the integration of multi-modal imaging data through iterative fits of a single underlying MFM in this realistic simulation framework.

Conceptual representation in bilinguals: the role of language specificity and conceptual change

Most prominent models of bilingual representation assume a degree of interconnection or shared representation at the conceptual level. However, in the context of linguistic and cultural specificity of human concepts, and given recent findings that reveal a considerable amount of bidirectional conceptual transfer and conceptual change in bilinguals, a particular challenge that bilingual models face is to account for non-equivalence or partial equivalence of L1 and L2 specific concepts in bilingual conceptual store. The aim of the current paper is to provide a state-of-the-art review of the available empirical evidence from the fields of psycholinguistics, cognitive, experimental, and cross-cultural psychology, and discuss how these may inform and develop further traditional and more recent accounts of bilingual conceptual representation. Based on a synthesis of the available evidence against theoretical postulates of existing models, I argue that the most coherent account of bilingual conceptual representation combines three fundamental assumptions. The first one is the distributed, multi-modal nature of representation. The second one concerns cross-linguistic and cross-cultural variation of concepts. The third one makes assumptions about the development of concepts, and the emergent links between those concepts and their linguistic instantiations.

Are we there yet? Exploring empowerment at the microscale in the South African wine industry

Empowerment is a standard but ambiguous element of development rhetoric and so, through the socially complex and contested terrain of South Africa, this paper explores its potential to contribute to inclusive development. Investigating micro-level engagements with the national strategy of Broad-Based Black Economic Empowerment (B-BBEE) in the South African wine industry highlights the limitations, but also potential, of this single domain approach. However, latent paternalism, entrenched interests and a ‘dislocated blackness’ maintain a complex racial politics that shapes both power relations and the opportunities for transformation within the industry. Nonetheless, while B-BBEE may not, in reality, be broad-based its manifestations are contributing to challenging racist structures and normalising changing attitudes. This paper concludes that, to be transformative, empowerment needs to be re-embedded within South Africa as a multi-scalar, multi-dimensional dialogue and, despite the continuation of structural constraints, positions the local as a critical scale at which to initiate broader social change.