Extraction of tidal channel networks from airborne scanning laser altimetry and aerial photography

The study of the morphodynamics of tidal channel networks is important because of their role in tidal propagation and the evolution of salt-marshes and tidal flats. Channel dimensions range from tens of metres wide and metres deep near the low water mark to only 20-30cm wide and 20cm deep for the smallest channels on the marshes. The conventional method of measuring the networks is cumbersome, involving manual digitising of aerial photographs. This paper describes a semi-automatic knowledge-based network extraction method that is being implemented to work using airborne scanning laser altimetry (and later aerial photography). The channels exhibit a width variation of several orders of magnitude, making an approach based on multi-scale line detection difficult. The processing therefore uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels using a distance-with-destination transform. Breaks in the networks are repaired by extending channel ends in the direction of their ends to join with nearby channels, using domain knowledge that flow paths should proceed downhill and that any network fragment should be joined to a nearby fragment so as to connect eventually to the open sea.

Nonlinear channel equalizer design using directional evolutionary multi-objective optimization

In this paper, a new equalizer learning scheme is introduced based on the algorithm of the directional evolutionary multi-objective optimization (EMOO). Whilst nonlinear channel equalizers such as the radial basis function (RBF) equalizers have been widely studied to combat the linear and nonlinear distortions in the modern communication systems, most of them do not take into account the equalizers' generalization capabilities. In this paper, equalizers are designed aiming at improving their generalization capabilities. It is proposed that this objective can be achieved by treating the equalizer design problem as a multi-objective optimization (MOO) problem, with each objective based on one of several training sets, followed by deriving equalizers with good capabilities of recovering the signals for all the training sets. Conventional EMOO which is widely applied in the MOO problems suffers from disadvantages such as slow convergence speed. Directional EMOO improves the computational efficiency of the conventional EMOO by explicitly making use of the directional information. The new equalizer learning scheme based on the directional EMOO is applied to the RBF equalizer design. Computer simulation demonstrates that the new scheme can be used to derive RBF equalizers with good generalization capabilities, i.e., good performance on predicting the unseen samples.

Blind channel estimation for multi-rate multicarrier DS/CDMA communications

Multi-rate multicarrier DS/CDMA is a potentially attractive multiple access method for future wireless communications networks that must support multimedia, and thus multi-rate, traffic. Several receiver structures exist for single-rate multicarrier systems, but little has been reported on multi-rate multicarrier systems. Considering that high-performance detection such as coherent demodulation needs the explicit knowledge of the channel, based on the finite-length chip waveform truncation, this paper proposes a subspace-based scheme for timing and channel estimation in multi-rate multicarrier DS/CDMA systems, which is applicable to both multicode and variable spreading factor systems. The performance of the proposed scheme for these two multi-rate systems is validated via numerical simulations. The effects of the finite-length chip waveform truncation on the performance of the proposed scheme is also analyzed theoretically.

Blind channel estimation in multi-rate multicarrier DS-CDMA systems

Multi-rate multicarrier DS-CDMA is a potentially attractive multiple access method for future broadband wireless multimedia networks that must support integrated voice/data traffic. This paper proposes a subspace based channel estimation scheme for multi-rate multicarrier DS-CDMA, which is applicable to both multicode and variable spreading factor systems. The performance of the proposed scheme for these two multi-rate systems is compared via numerical simulations.

Blind channel acquisition and channel estimation for multi-rate multicarrier DS-CDMA communications

Multi-rate multicarrier DS-CDMA is a potentially attractive multiple access method for future wireless networks that must support multimedia, and thus multi-rate, traffic. Considering that high performance detection such as coherent demodulation needs the explicit knowledge of the channel, this paper proposes a subspace-based blind adaptive algorithm for timing acquisition and channel estimation in asynchronous multirate multicarrier DS-CDMA systems, which is applicable to both multicode and variable spreading factor systems.

Compliant Multi-electrode Micro-channel Array for Recording Afferent Nerve Activity

We have fabricated a compliant neural interface to record afferent nerve activity. Stretchable gold electrodes were evaporated on a polydimethylsiloxane (PDMS) substrate and were encapsulated using photo-patternable PDMS. The built-in microstructure of the gold film on PDMS allows the electrodes to twist and flex repeatedly, without loss of electrical conductivity. PDMS microchannels (5mm long, 100μm wide, 100μm deep) were then plasma bonded irreversibly on top of the electrode array to define five parallel-conduit implants. The soft gold microelectrodes have a low impedance of ~200kΩ at the 1kHz frequency range. Teased nerves from the L6 dorsal root of an anaesthetized Sprague Dawley rat were threaded through the microchannels. Acute tripolar recordings of cutaneous activity are demonstrated, from multiple nerve rootlets simultaneously. Confinement of the axons within narrow microchannels allows for reliable recordings of low amplitude afferents. This electrode technology promises exciting applications in neuroprosthetic devices including bladder fullness monitors and peripheral nervous system implants.

Multi-agent collaboration for decision support in shared zones of intelligent buildings

In domain of intelligent buildings, saving energy in buildings and increasing preferences of occupants are two important factors. These factors are the important keys for evaluating the performance of work environment. In recent years, many researchers combine these areas to create the system that can change from original to the modern work environment called intelligent work environment. Due to advance of agent technology, it has received increasing attention in the area of intelligent pervasive environments. In this paper, we review several issues in intelligent buildings, with respect to the implementation of control system for intelligent buildings via multi-agent systems. Furthermore, we present the MASBO (Multi-Agent System for Building cOntrol) that has been implemented for controlling the building facilities to reach the balancing between energy efficiency and occupant’s comfort. In addition to enhance the MASBO system, the collaboration through negotiation among agents is presented.

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.

Supporting multi-organisational collaborative groups in the public sector

In this paper, the issues that arise in multi-organisational collaborative groups (MOCGs) in the public sector are discussed and how a technology-based group support system (GSS) could assist individuals within these groups. MOCGs are commonly used in the public sector to find solutions to multifaceted social problems. Finding solutions for such problems is difficult because their scope is outside the boundary of a single government agency. The standard approach to solving such problems is collaborative involving a diverse range of stakeholders. Collaborative working can be advantageous but it also introduces its own pressures. Conflicts can arise due to the multiple contexts and goals of group members and the organisations that they represent. Trust, communication and a shared interface are crucial to making any significant progress. A GSS could support these elements.

Extraction of tidal channel networks from aerial photographs alone and combined with laser altimetry

Tidal channel networks play an important role in the intertidal zone, exerting substantial control over the hydrodynamics and sediment transport of the region and hence over the evolution of the salt marshes and tidal flats. The study of the morphodynamics of tidal channels is currently an active area of research, and a number of theories have been proposed which require for their validation measurement of channels over extensive areas. Remotely sensed data provide a suitable means for such channel mapping. The paper describes a technique that may be adapted to extract tidal channels from either aerial photographs or LiDAR data separately, or from both types of data used together in a fusion approach. Application of the technique to channel extraction from LiDAR data has been described previously. However, aerial photographs of intertidal zones are much more commonly available than LiDAR data, and most LiDAR flights now involve acquisition of multispectral images to complement the LiDAR data. In view of this, the paper investigates the use of multispectral data for semiautomatic identification of tidal channels, firstly from only aerial photographs or linescanner data, and secondly from fused linescanner and LiDAR data sets. A multi-level, knowledge-based approach is employed. The algorithm based on aerial photography can achieve a useful channel extraction, though may fail to detect some of the smaller channels, partly because the spectral response of parts of the non-channel areas may be similar to that of the channels. The algorithm for channel extraction from fused LiDAR and spectral data gives an increased accuracy, though only slightly higher than that obtained using LiDAR data alone. The results illustrate the difficulty of developing a fully automated method, and justify the semi-automatic approach adopted.

Uses of airborne scanning laser altimetry for river flood modelling and coastal geomorphology

Two ongoing projects at ESSC that involve the development of new techniques for extracting information from airborne LiDAR data and combining this information with environmental models will be discussed. The first project in conjunction with Bristol University is aiming to improve 2-D river flood flow models by using remote sensing to provide distributed data for model calibration and validation. Airborne LiDAR can provide such models with a dense and accurate floodplain topography together with vegetation heights for parameterisation of model friction. The vegetation height data can be used to specify a friction factor at each node of a model’s finite element mesh. A LiDAR range image segmenter has been developed which converts a LiDAR image into separate raster maps of surface topography and vegetation height for use in the model. Satellite and airborne SAR data have been used to measure flood extent remotely in order to validate the modelled flood extent. Methods have also been developed for improving the models by decomposing the model’s finite element mesh to reflect floodplain features such as hedges and trees having different frictional properties to their surroundings. Originally developed for rural floodplains, the segmenter is currently being extended to provide DEMs and friction parameter maps for urban floods, by fusing the LiDAR data with digital map data. The second project is concerned with the extraction of tidal channel networks from LiDAR. These networks are important features of the inter-tidal zone, and play a key role in tidal propagation and in the evolution of salt-marshes and tidal flats. The study of their morphology is currently an active area of research, and a number of theories related to networks have been developed which require validation using dense and extensive observations of network forms and cross-sections. The conventional method of measuring networks is cumbersome and subjective, involving manual digitisation of aerial photographs in conjunction with field measurement of channel depths and widths for selected parts of the network. A semi-automatic technique has been developed to extract networks from LiDAR data of the inter-tidal zone. A multi-level knowledge-based approach has been implemented, whereby low level algorithms first extract channel fragments based mainly on image properties then a high level processing stage improves the network using domain knowledge. The approach adopted at low level uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels. The higher level processing includes a channel repair mechanism.

The Ca(v)2.3 calcium channel antagonist SNX-482 reduces dorsal horn neuronal responses in a rat model of chronic neuropathic pain

Neuropathic pain is a difficult state to treat, characterized by alterations in sensory processing that can include allodynia (touch-evoked pain). Evidence exists for nerve damage-induced plasticity in both transmission and modulatory systems, including changes in voltage-dependent calcium channel (VDCC) expression and function; however, the role of Ca(v)2.3 calcium channels has not clearly been defined. Here, the effects of SNX-482, a selective Ca(v)2.3 antagonist, on sensory transmission at the spinal cord level have been investigated in the rat. The spinal nerve ligation (SNL) model of chronic neuropathic pain [Kim & Chung, (1992) Pain, 50, 355-363] was used to induce mechanical allodynia, as tested on the ipsilateral hindpaw. In vivo electrophysiological measurements of dorsal horn neuronal responses to innocuous and noxious electrical and natural stimuli were made after SNL and compared to sham-operated animals. Spinal SNX-482 (0.5-4 mu g/50 mu L) exerted dose-related inhibitions of noxious C-fibre- and A delta-fibre-mediated neuronal responses in conditions of neuropathy, but not in sham-operated animals. Measures of spinal cord hyperexcitability and nociception were most susceptible to SNX-482. In contrast, non-noxious A beta-mediated responses were not affected by SNX-482. Moreover, responses to innocuous mechanical and also thermal stimuli were more sensitive to SNX-482 in SNL than control animals. This study is the first to demonstrate an antinociceptive role for SNX-482-sensitive channels in dorsal horn neurons during neuropathy. These data are consistent with plasticity in Ca(V)2.3 calcium channel expression and suggest a potential selective target to reduce nociceptive transmission during conditions of nerve damage.

From dichotic listening to the irrelevant sound effect: a behavioural and neuroimaging analysis of the processing of unattended speech

The assumption that ignoring irrelevant sound in a serial recall situation is identical to ignoring a non-target channel in dichotic listening is challenged. Dichotic listening is open to moderating effects of working memory capacity (Conway et al., 2001) whereas irrelevant sound effects (ISE) are not (Beaman, 2004). A right ear processing bias is apparent in dichotic listening, whereas the bias is to the left ear in the ISE (Hadlington et al., 2004). Positron emission tomography (PET) imaging data (Scott et al., 2004, submitted) show bilateral activation of the superior temporal gyrus (STG) in the presence of intelligible, but ignored, background speech and right hemisphere activation of the STG in the presence of unintelligible background speech. It is suggested that the right STG may be involved in the ISE and a particularly strong left ear effect might occur because of the contralateral connections in audition. It is further suggested that left STG activity is associated with dichotic listening effects and may be influenced by working memory span capacity. The relationship of this functional and neuroanatomical model to known neural correlates of working memory is considered.

A fuzzy multi-criteria decision approach for enhanced auto-tracking of seismic events

The main activity carried out by the geophysicist when interpreting seismic data, in terms of both importance and time spent is tracking (or picking) seismic events. in practice, this activity turns out to be rather challenging, particularly when the targeted event is interrupted by discontinuities such as geological faults or exhibits lateral changes in seismic character. In recent years, several automated schemes, known as auto-trackers, have been developed to assist the interpreter in this tedious and time-consuming task. The automatic tracking tool available in modem interpretation software packages often employs artificial neural networks (ANN's) to identify seismic picks belonging to target events through a pattern recognition process. The ability of ANNs to track horizons across discontinuities largely depends on how reliably data patterns characterise these horizons. While seismic attributes are commonly used to characterise amplitude peaks forming a seismic horizon, some researchers in the field claim that inherent seismic information is lost in the attribute extraction process and advocate instead the use of raw data (amplitude samples). This paper investigates the performance of ANNs using either characterisation methods, and demonstrates how the complementarity of both seismic attributes and raw data can be exploited in conjunction with other geological information in a fuzzy inference system (FIS) to achieve an enhanced auto-tracking performance.