A tool for replay and analysis of gaze-enhanced multiparty sessions captured in immersive collaborative environments

A desktop tool for replay and analysis of gaze-enhanced multiparty virtual collaborative sessions is described. We linked three CAVE (TM)-like environments, creating a multiparty collaborative virtual space where avatars are animated with 3D gaze as well as head and hand motions in real time. Log files are recorded for subsequent playback and analysis Using the proposed software tool. During replaying the user can rotate the viewpoint and navigate in the simulated 3D scene. The playback mechanism relies on multiple distributed log files captured at every site. This structure enables an observer to experience latencies of movement and information transfer for every site as this is important fir conversation analysis. Playback uses an event-replay algorithm, modified to allow fast traversal of the scene by selective rendering of nodes, and to simulate fast random access. The tool's is analysis module can show each participant's 3D gaze points and areas where gaze has been concentrated.

Optimising memory usage in n-tuple neural networks

The use of n-tuple or weightless neural networks as pattern recognition devices is well known (Aleksander and Stonham, 1979). They have some significant advantages over the more common and biologically plausible networks, such as multi-layer perceptrons; for example, n-tuple networks have been used for a variety of tasks, the most popular being real-time pattern recognition, and they can be implemented easily in hardware as they use standard random access memories. In operation, a series of images of an object are shown to the network, each being processed suitably and effectively stored in a memory called a discriminator. Then, when another image is shown to the system, it is processed in a similar manner and the system reports whether it recognises the image; is the image sufficiently similar to one already taught? If the system is to be able to recognise and discriminate between m-objects, then it must contain m-discriminators. This can require a great deal of memory. This paper describes various ways in which memory requirements can be reduced, including a novel method for multiple discriminator n-tuple networks used for pattern recognition. By using this method, the memory normally required to handle m-objects can be used to recognise and discriminate between 2^m — 2 objects.

Auto-associative memory using n-tuple techniques

The use of n-tuple or weightless neural networks as pattern recognition devices has been well documented. They have a significant advantages over more common networks paradigms, such as the multilayer perceptron in that they can be easily implemented in digital hardware using standard random access memories. To date, n-tuple networks have predominantly been used as fast pattern classification devices. The paper describes how n-tuple techniques can be used in the hardware implementation of a general auto-associative network.

Random-walk-based characterisation of multiple access interference in a DS/SSMA system

The problem of calculating the probability of error in a DS/SSMA system has been extensively studied for more than two decades. When random sequences are employed some conditioning must be done before the application of the central limit theorem is attempted, leading to a Gaussian distribution. The authors seek to characterise the multiple access interference as a random-walk with a random number of steps, for random and deterministic sequences. Using results from random-walk theory, they model the interference as a K-distributed random variable and use it to calculate the probability of error in the form of a series, for a DS/SSMA system with a coherent correlation receiver and BPSK modulation under Gaussian noise. The asymptotic properties of the proposed distribution agree with other analyses. This is, to the best of the authors' knowledge, the first attempt to propose a non-Gaussian distribution for the interference. The modelling can be extended to consider multipath fading and general modulation

Intelligent wireless web services: context-aware computing in construction-logistics supply chain

The construction industry has incurred a considerable amount of waste as a result of poor logistics supply chain network management. Therefore, managing logistics in the construction industry is critical. An effective logistic system ensures delivery of the right products and services to the right players at the right time while minimising costs and rewarding all sectors based on value added to the supply chain. This paper reports on an on-going research study on the concept of context-aware services delivery in the construction project supply chain logistics. As part of the emerging wireless technologies, an Intelligent Wireless Web (IWW) using context-aware computing capability represents the next generation ICT application to construction-logistics management. This intelligent system has the potential of serving and improving the construction logistics through access to context-specific data, information and services. Existing mobile communication deployments in the construction industry rely on static modes of information delivery and do not take into account the worker’s changing context and dynamic project conditions. The major problems in these applications are lack of context-specificity in the distribution of information, services and other project resources, and lack of cohesion with the existing desktop based ICT infrastructure. The research works focus on identifying the context dimension such as user context, environmental context and project context, selection of technologies to capture context-parameters such wireless sensors and RFID, selection of supporting technologies such as wireless communication, Semantic Web, Web Services, agents, etc. The process of integration of Context-Aware Computing and Web-Services to facilitate the creation of intelligent collaboration environment for managing construction logistics will take into account all the necessary critical parameters such as storage, transportation, distribution, assembly, etc. within off and on-site project.

Calibration of structure in a distributed forecasting model for a semiarid flash flood: dynamic surface storage and channel roughness

Flash floods pose a significant danger for life and property. Unfortunately, in arid and semiarid environment the runoff generation shows a complex non-linear behavior with a strong spatial and temporal non-uniformity. As a result, the predictions made by physically-based simulations in semiarid areas are subject to great uncertainty, and a failure in the predictive behavior of existing models is common. Thus better descriptions of physical processes at the watershed scale need to be incorporated into the hydrological model structures. For example, terrain relief has been systematically considered static in flood modelling at the watershed scale. Here, we show that the integrated effect of small distributed relief variations originated through concurrent hydrological processes within a storm event was significant on the watershed scale hydrograph. We model these observations by introducing dynamic formulations of two relief-related parameters at diverse scales: maximum depression storage, and roughness coefficient in channels. In the final (a posteriori) model structure these parameters are allowed to be both time-constant or time-varying. The case under study is a convective storm in a semiarid Mediterranean watershed with ephemeral channels and high agricultural pressures (the Rambla del Albujón watershed; 556 km 2 ), which showed a complex multi-peak response. First, to obtain quasi-sensible simulations in the (a priori) model with time-constant relief-related parameters, a spatially distributed parameterization was strictly required. Second, a generalized likelihood uncertainty estimation (GLUE) inference applied to the improved model structure, and conditioned to observed nested hydrographs, showed that accounting for dynamic relief-related parameters led to improved simulations. The discussion is finally broadened by considering the use of the calibrated model both to analyze the sensitivity of the watershed to storm motion and to attempt the flood forecasting of a stratiform event with highly different behavior.

Varieties of semantic ‘access’ deficit in Wernicke’s aphasia and semantic aphasia

Comprehension deficits are common in stroke aphasia, including in cases with (i) semantic aphasia (SA), characterised by poor executive control of semantic processing across verbal and nonverbal modalities, and (ii) Wernicke’s aphasia (WA), associated with poor auditory-verbal comprehension and repetition, plus fluent speech with jargon. However, the varieties of these comprehension problems, and their underlying causes, are not well-understood. Both patient groups exhibit some type of semantic ‘access’ deficit, as opposed to the ‘storage’ deficits observed in semantic dementia. Nevertheless, existing descriptions suggest these patients might have different varieties of ‘access’ impairment – related to difficulty resolving competition (in SA) vs. initial activation of concepts from sensory inputs (in WA). We used a case-series design to compare WA and SA patients on Warrington’s paradigmatic assessment of semantic ‘access’ deficits. In these verbal and non-verbal matching tasks, a small set of semantically-related items are repeatedly presented over several cycles so that the target on one trial becomes a distractor on another (building up interference and eliciting semantic ‘blocking’ effects). WA and SA patients were distinguished according to lesion location in the temporal cortex, but in each group, some individuals had additional prefrontal damage. Both of these aspects of lesion variability – one that mapped onto classical ‘syndromes’ and one that did not – predicted aspects of the semantic ‘access’ deficit. Both SA and WA cases showed multimodal semantic impairment, although as expected the WA group showed greater deficits on auditory-verbal than picture judgements. Distribution of damage in the temporal lobe was crucial for predicting the initially beneficial effects of stimulus repetition: WA cases showed initial improvement with repetition of words and pictures, while in SA, semantic access was initially good but declined in the face of competition from previous targets. Prefrontal damage predicted the harmful effects of repetition: the ability to re-select both word and picture targets in the face of mounting competition was linked to left prefrontal damage in both groups. Therefore, SA and WA patients have partially distinct impairment of semantic ‘access’ but, across these syndromes, prefrontal lesions produce declining comprehension with repetition in both verbal and non-verbal tasks.

Efficient biometric and password based mutual authentication for consumer USB mass storage devices

A Universal Serial Bus (USB) Mass Storage Device (MSD), often termed a USB flash drive, is ubiquitously used to store important information in unencrypted binary format. This low cost consumer device is incredibly popular due to its size, large storage capacity and relatively high transfer speed. However, if the device is lost or stolen an unauthorized person can easily retrieve all the information. Therefore, it is advantageous in many applications to provide security protection so that only authorized users can access the stored information. In order to provide security protection for a USB MSD, this paper proposes a session key agreement protocol after secure user authentication. The main aim of this protocol is to establish session key negotiation through which all the information retrieved, stored and transferred to the USB MSD is encrypted. This paper not only contributes an efficient protocol, but also does not suffer from the forgery attack and the password guessing attack as compared to other protocols in the literature. This paper analyses the security of the proposed protocol through a formal analysis which proves that the information is stored confidentially and is protected offering strong resilience to relevant security attacks. The computational cost and communication cost of the proposed scheme is analyzed and compared to related work to show that the proposed scheme has an improved tradeoff for computational cost, communication cost and security.

Optimal power management strategy for energy storage with stochastic loads

In this paper, a power management strategy (PMS) has been developed for the control of energy storage in a system subjected to loads of random duration. The PMS minimises the costs associated with the energy consumption of specific systems powered by a primary energy source and equipped with energy storage, under the assumption that the statistical distribution of load durations is known. By including the variability of the load in the cost function, it was possible to define the optimality criteria for the power flow of the storage. Numerical calculations have been performed obtaining the control strategies associated with the global minimum in energy costs, for a wide range of initial conditions of the system. The results of the calculations have been tested on a MATLAB/Simulink model of a rubber tyre gantry (RTG) crane equipped with a flywheel energy storage system (FESS) and subjected to a test cycle, which corresponds to the real operation of a crane in the Port of Felixstowe. The results of the model show increased energy savings and reduced peak power demand with respect to existing control strategies, indicating considerable potential savings for port operators in terms of energy and maintenance costs.