Experimental test of a robust formation controller for marine unmanned surface vessels

Experiments with two formation controllers for marine unmanned surface vessels are reported. The formation controllers are designed using the nonlinear robust model-based sliding mode approach. The marine vehicles can operate in arbitrary formation configurations by using two leader-follower control schemes. For the design of these controller schemes 3 degrees of freedom (DOFs) of surge, sway, and yaw are assumed in the planar motion of the marine surface vessels. Each vessel only has two actuators; therefore, the vessels are underactuated and the lack of a kinematic constraint puts them into the holonomic system category. In this work, the position of a control point on the vessel is controlled, and the orientation dynamics is not directly controlled. Therefore, there is a potential for an oscillatory yaw motion to occur. It is shown that the orientation dynamics, as the internal dynamics of this underactuated system, is stable, i.e., the follower vehicle does not oscillate about its control point during the formation maneuvers. The proposed formation controller relies only on the state information obtained from the immediate neighbors of the vessel and the vessel itself. The effectiveness and robustness of formation control laws in the presence of parameter uncertainty and environmental disturbances are demonstrated by using both simulations and field experiments. The experiments were performed in a natural environment on a lake using a small test boat, and show robust performance to parameter uncertainty and disturbance. This paper reports the first experimental verification of the above mentioned approach, whose unique features are the use of a control point, the zero-dynamic stability analysis, the use of leader-follower method and a nonlinear robust control approach.     

Monte Carlo techniques for phrase-based translation

Recent advances in statistical machine translation have used approximate beam search for NP-complete inference within probabilistic translation models. We present an alternative approach of sampling from the posterior distribution defined by a translation model. We define a novel Gibbs sampler for sampling translations given a source sentence and show that it effectively explores this posterior distribution. In doing so we overcome the limitations of heuristic beam search and obtain theoretically sound solutions to inference problems such as finding the maximum probability translation and minimum risk training and decoding.     

Systems modelling for effective mine water management

Concerns about the difficulties in securing water have led the Australian coal mining industry to seek innovative ways to improve its water management and to adopt novel strategies that will lead to less water being used and more water being reused. Simulation tools are essential to assess current water management performance and to predict the efficiency of potential strategies. As water systems on coal mines are complex and consist of various inter-connected elements, a systems approach was selected, which views mine site water management as a system that obtains water from various sources (surface, groundwater), provides sufficient water of suitable quality to the mining tasks (coal beneficiation, dust suppression, underground operations) and maintains environmental performance. In this paper, the model is described and its calibration is illustrated. The results of applying the model for the comparison of the water balances of 7 coal mines in the northern Bowen Basin (Queensland, Australia) are presented. The model is used to assess the impact of applying specific water management strategies. Results show that a simple systems model is an appropriate tool for assessing site performance, for providing guidance to improve performance through strategic planning, and for guiding adoption of site objectives.     

Creating non-minimal triangulations for use in inference in mixed stochastic/deterministic graphical models

We demonstrate that certain large-clique graph triangulations can be useful for reducing computational requirements when making queries on mixed stochastic/deterministic graphical models. This is counter to the conventional wisdom that triangulations that minimize clique size are always most desirable for use in computing queries on graphical models. Many of these large-clique triangulations are non-minimal and are thus unattainable via the popular elimination algorithm. We introduce ancestral pairs as the basis for novel triangulation heuristics and prove that no more than the addition of edges between ancestral pairs needs to be considered when searching for state space optimal triangulations in such graphs. Empirical results on random and real world graphs are given. We also present an algorithm and correctness proof for determining if a triangulation can be obtained via elimination, and we show that the decision problem associated with finding optimal state space triangulations in this mixed setting is NP-complete.     

Trading Off Cache Capacity for Low-Voltage Operation

Two proposed techniques let microprocessors operate at low voltages despite high memory-cell failure rates. They identify and disable defective portions of the cache at two granularities: individual words or pairs of bits. Both techniques use the entire cache during high-voltage operation while sacrificing cache capacity during low-voltage operation to reduce the minimum voltage below 500 mV.     

An investigation of multiphase CFD modelling of a lateral sloshing tank

A near-resonant, sway-induced sloshing flow in a rectangular tank is used to compare a homogeneous and inhomogeneous multiphase approach for fluid density and viscosity in a commercial CFD code. Dimensional analysis of the relative motion between the phases suggests the application of an inhomogeneous multiphase model whereas previous published work has used the computationally cheaper homogeneous (or average property) approach. The comparison between the computational and experimental results shows that the homogeneous model tends to underestimate the experimental peak pressures by up to 50%. The inhomogeneous multiphase model gives good agreement with the experimental pressure data. Examination of the relative velocity at the fluid interface confirms that the inhomogeneous model is the appropriate model to use for the simulation of a violent sloshing flow.     

Culture & biometrics: regional differences in the perception of biometric authentication technologies

Previous research has identified user concerns about biometric authentication technology, but most of this research has been conducted in European contexts. There is a lack of research that has investigated attitudes towards biometric technology in other cultures. To address this issue, data from India, South Africa and the United Kingdom were collected and compared. Cross-cultural attitudinal differences were seen, with Indian respondents viewing biometrics most positively while respondents from the United Kingdom were the least likely to have a positive opinion about biometrics. Multiple barriers to the acceptance of biometric technology were identified with data security and health and safety fears having the greatest overall impact on respondents’ attitudes towards biometrics. The results of this investigation are discussed with reference to Hofstede’s cultural dimensions and theories of technology acceptance. It is argued that contextual issues specific to each country provide a better explanation of the results than existing theories based on Hofstede’s model. We conclude that cultural differences have an impact on the way biometric systems will be used and argue that these factors should be taken into account during the design and implementation of biometric systems.     

Narrow Band FLIP for Liquid Simulations

The Fluid Implicit Particle method (FLIP) for liquid simulations uses particles to reduce numerical dissipation and provide important visual cues for events like complex splashes and small‐scale features near the liquid surface. Unfortunately, FLIP simulations can be computationally expensive, because they require a dense sampling of particles to fill the entire liquid volume. Furthermore, the vast majority of these FLIP particles contribute nothing to the fluid's visual appearance, especially for larger volumes of liquid. We present a method that only uses FLIP particles within a narrow band of the liquid surface, while efficiently representing the remaining inner volume on a regular grid. We show that a naïve realization of this idea introduces unstable and uncontrollable energy fluctuations, and we propose a novel coupling scheme between FLIP particles and regular grid which overcomes this problem. Our method drastically reduces the particle count and simulation times while yielding results that are nearly indistinguishable from regular FLIP simulations. Our approach is easy to integrate into any existing FLIP implementation.