Models and algorithms for detection and tracking of coordinated groups

In this paper, we describe models and algorithms for detection and tracking of group and individual targets. We develop two novel group dynamical models, within a continuous time setting, that aim to mimic behavioural properties of groups. We also describe two possible ways of modeling interactions between closely using Markov Random Field (MRF) and repulsive forces. These can be combined together with a group structure transition model to create realistic evolving group models. We use a Markov Chain Monte Carlo (MCMC)-Particles Algorithm to perform sequential inference. Computer simulations demonstrate the ability of the algorithm to detect and track targets within groups, as well as infer the correct group structure over time. ©2008 IEEE.

A novel design of Thermally Actuated Magnetization Flux pump for high temperature superconducting bulks

High temperature superconductors, such as melt-processed YBCO bulks, have great advantages on trapping strong magnetic fields in liquid nitrogen. To enable them to function well, there are some traditional ways of magnetizing them, in which the YBCO bulks are magnetized instantly under a very strong source of magnetic field. These ways would consume great amounts of power to make the superconductors trap as much field as possible. Thermally Actuated Magnetization (TAM) Flux pump has been proved a perfect substitution for these expensive methods by using a relatively small magnet as the source. In this way, the field is developed gradually over many pulses. Unlike conventional flux pumping ways, the TAM does not drive the superconductor normal during the process of magnetization. In former experiments for the flux pump, some fundamental tests were done. In this paper, the experiment system is advanced to a new level with better temperature control to the thermal waves moving in the Gadolinium and with less air gap for the flux lines sweeping through the superconductor. This experiment system F leads to a stronger accumulation of the magnetic field trapped in the YBCO bulk. We also tried different ways of sending the thermal waves and found out that the pumping effect is closely related to the power of the heaters and the on and off time. © 2010 IEEE.

Characterisation and simulation of asphalt road surfaces

Accurate simulation of rolling-tyre vibrations, and the associated noise, requires knowledge of road-surface topology. Full scans of the surface types in common use are, however, not widely available, and are likely to remain so. Ways of producing simulated surfaces from incomplete starting information are thus needed. In this paper, a simulation methodology based solely on line measurements is developed, and validated against a full two-dimensional height map of a real asphalt surface. First the tribological characteristics-asperity height, curvature and nearest-neighbour distributions-of the real surface are analysed. It is then shown that a standard simulation technique, which matches the (isotropic) spectrum and the probability distribution of the height measurements, is unable to reproduce these characteristics satisfactorily. A modification, whereby the inherent granularity of the surface is enforced at the initialisation stage, is introduced, and found to produce simulations whose tribological characteristics are in excellent agreement with the measurements. This method will thus make high-fidelity tyre-vibration calculations feasible for researchers with access to line-scan data only. In addition, the approach to surface tribological characterisation set out here provides a template for efficient cataloguing of road textures, as long as the resulting information can subsequently be used to produce sample realisations. A third simulation algorithm, which successfully addresses this requirement, is therefore also presented. © 2011 Elsevier B.V.

Natural actor and belief critic: Reinforcement algorithm for learning parameters of dialogue systems modelled as POMDPs

This article presents a novel algorithm for learning parameters in statistical dialogue systems which are modeled as Partially Observable Markov Decision Processes (POMDPs). The three main components of a POMDP dialogue manager are a dialogue model representing dialogue state information; a policy that selects the system's responses based on the inferred state; and a reward function that specifies the desired behavior of the system. Ideally both the model parameters and the policy would be designed to maximize the cumulative reward. However, while there are many techniques available for learning the optimal policy, no good ways of learning the optimal model parameters that scale to real-world dialogue systems have been found yet. The presented algorithm, called the Natural Actor and Belief Critic (NABC), is a policy gradient method that offers a solution to this problem. Based on observed rewards, the algorithm estimates the natural gradient of the expected cumulative reward. The resulting gradient is then used to adapt both the prior distribution of the dialogue model parameters and the policy parameters. In addition, the article presents a variant of the NABC algorithm, called the Natural Belief Critic (NBC), which assumes that the policy is fixed and only the model parameters need to be estimated. The algorithms are evaluated on a spoken dialogue system in the tourist information domain. The experiments show that model parameters estimated to maximize the expected cumulative reward result in significantly improved performance compared to the baseline hand-crafted model parameters. The algorithms are also compared to optimization techniques using plain gradients and state-of-the-art random search algorithms. In all cases, the algorithms based on the natural gradient work significantly better. © 2011 ACM.

An evaluation of a new product data model

Engineering companies face many challenges today such as increased competition, higher expectations from consumers and decreasing product lifecycle times. This means that product development times must be reduced to meet these challenges. Concurrent engineering, reuse of engineering knowledge and the use of advanced methods and tools are among the ways of reducing product development times. Concurrent engineering is crucial in making sure that the products are designed with all issues considered simultaneously. The reuse of engineering knowledge allows existing solutions to be reused. It can also help to avoid the mistakes made in previous designs. Computer-based tools are used to store information, automate tasks, distribute work, perform simulation and so forth. This research concerns the evaluation of tools that can be used to support the design process. These tools are evaluated in terms of the capture of information generated during the design process. This information is vital to allow the reuse of knowledge. Present CAD systems store only information on the final definition of the product such as geometry, materials and manufacturing processes. Product Data Management (PDM) systems can manage all this CAD information along with other product related information. The research includes the evaluation of two PDM systems, Windchill and Metaphase, using the design of a single-handed water tap as a case study. The two PDMs were then compared to PROSUS/DDM. PROSUS is the Process-Based Support System proposed by [Blessing 94] using the same case study. The Design Data Model is the product data model that includes PROSUS. The results look promising. PROSUS/DDM is able to capture most design information and structure and present it logically. The design process and product information is related and stored within the DDM structure. The PDMs can capture most design information, but information from early stages of design is stored only as unstructured documentation. Some problems were found with PROSUS/DDM. A proposal is made that may make it possible to resolve these problems, but this will require further research.

Computer-based selection of joining processes

The assembly of any manufactured product involves joining. This paper describes ways of selecting processes for joining. The method allows discrimination of the joint geometry, joint loading, material, and other attributes of the joint itself, identifying the subset of available processes capable of meeting a given set of design constraints. A relational database containing data-tables for joining processes, materials to be joined, and joint geometry and mode of loading, allows the attributes of each of these to be stored in an appropriate format, and permits links to be created between those that are related. A search engine isolates the processes that meet design requirements on material, joint geometry and loading. The method is illustrated in Part 2 by case studies, utilising software that embodies the method.

Mathematical relationships between representations of structure in linear interconnected dynamical systems

A dynamical system can exhibit structure on multiple levels. Different system representations can capture different elements of a dynamical system's structure. We consider LTI input-output dynamical systems and present four representations of structure: complete computational structure, subsystem structure, signal structure, and input output sparsity structure. We then explore some of the mathematical relationships that relate these different representations of structure. In particular, we show that signal and subsystem structure are fundamentally different ways of representing system structure. A signal structure does not always specify a unique subsystem structure nor does subsystem structure always specify a unique signal structure. We illustrate these concepts with a numerical example. © 2011 AACC American Automatic Control Council.

I did that! Measuring users' experience of agency in their own actions

Cognitive neuroscience defines the sense of agency as the experience of controlling one's own actions and, through this control, affecting the external world. We believe that the sense of personal agency is a key factor in how people experience interactions with technology. This paper draws on theoretical perspectives in cognitive neuroscience and describes two implicit methods through which personal agency can be empirically investigated. We report two experiments applying these methods to HCI problems. One shows that a new input modality - skin-based interaction - can substantially increase users' sense of agency. The second demonstrates that variations in the parameters of assistance techniques such as predictive mouse acceleration can have a significant impact on users' sense of agency. The methods presented provide designers with new ways of evaluating and refining empowering interaction techniques and interfaces, in which users experience an instinctive sense of control and ownership over their actions. Copyright 2012 ACM.

Predictive control of a Boeing 747 aircraft using an FPGA

New embedded predictive control applications call for more eficient ways of solving quadratic programs (QPs) in order to meet demanding real-time, power and cost requirements. A single precision QP-on-a-chip controller is proposed, implemented in afield-programmable gate array (FPGA) with an iterative linear solver at its core. A novel offline scaling procedure is introduced to aid the convergence of the reduced precision solver. The feasibility of the proposed approach is demonstrated with a real-time hardware-in-the-loop (HIL) experimental setup where an ML605 FPGA board controls a nonlinear model of a Boeing 747 aircraft running on a desktop PC through an Ethernet link. Simulations show that the quality of the closed-loop control and accuracy of individual solutions is competitive with a conventional double precision controller solving linear systems using a Riccati recursion. © 2012 IFAC.

Dialogical strategies for orchestrating strategic innovation networks: the case of the Internet of Things

Strategic innovation has been shown to provide significant value for organisations whilst at the same time challenging traditional ways of thinking and working. There is less known, however, as to how organisations collaborate in innovation networks to achieve strategic innovation. In this paper we explore how innovation networks are orchestrated in developing a strategic innovation initiative around the Internet of Things. We show how a hub actor brings together a diverse group of actors to initially create and subsequently orchestrate the strategic innovation network through the employ of three dialogical strategies, namely persuasive projection, reflective development, and definitional control. Further, we illuminate how different types of legitimacy are established through these various dialogical strategies in orchestrating strategic innovation networks.