The role of graduality for referring expression generation in visual scenes

Referring Expression Generation (reg) algorithms, a core component of systems that generate text from non-linguistic data, seek to identify domain objects using natural language descriptions. While reg has often been applied to visual domains, very few approaches deal with the problem of fuzziness and gradation. This paper discusses these problems and how they can be accommodated to achieve a more realistic view of the task of referring to objects in visual scenes.peer-reviewe

Clustering and Uncertainty in Perfect Chaos Systems

The goal of this investigation was to derive strictly new properties of chaotic systems and their mutual relations. The generalized Fokker-Planck equation with a non stationary diffusion has been derived and used for chaos analysis. An anomalous transport turned out to be natural property of this equation. A nonlinear dispersion of the considered motion allowed to find a principal consequence: a chaotic system with uniform dynamic properties tends to unstable clustering. Small fluctuations of particles density increase by time and form attractors and stochastic islands even if the initial transport properties have uniform distribution. It was shown that an instability of phase trajectories leads to the nonlinear dispersion law and consequently to a space instability. A fixed boundary system was considered, using a standard Fokker-Planck equation. We have derived that such a type of dynamic systems has a discrete diffusive and energy spectra. It was shown that phase space diffusion is the only parameter that defines a dynamic accuracy in this case. The uncertainty relations have been obtained for conjugate phase space variables with account of transport properties. Given results can be used in the area of chaotic systems modelling and turbulence investigation.Comment: 9 pages, Journal of Chaos, vol. 2014, open access: http://www.hindawi.com/journals/jcha/2014/292096

Coherent Price Systems and Uncertainty-Neutral Valuation

We consider fundamental questions of arbitrage pricing arising when the uncertainty model is given by a set of possible mutually singular probability measures. With a single probability model, essential equivalence between the absence of arbitrage and the existence of an equivalent martingale measure is a folk theorem, see Harrison and Kreps (1979). We establish a microeconomic foundation of sublinear price systems and present an extension result. In this context we introduce a prior dependent notion of marketed spaces and viable price systems. We associate this extension with a canonically altered concept of equivalent symmetric martingale measure sets, in a dynamic trading framework under absence of prior depending arbitrage. We prove the existence of such sets when volatility uncertainty is modeled by a stochastic differential equation, driven by Peng's G-Brownian motions

Safety Verification of Fault Tolerant Goal-based Control Programs with Estimation Uncertainty

Fault tolerance and safety verification of control systems that have state variable estimation uncertainty are essential for the success of autonomous robotic systems. A software control architecture called mission data system, developed at the Jet Propulsion Laboratory, uses goal networks as the control program for autonomous systems. Certain types of goal networks can be converted into linear hybrid systems and verified for safety using existing symbolic model checking software. A process for calculating the probability of failure of certain classes of verifiable goal networks due to state estimation uncertainty is presented. A verifiable example task is presented and the failure probability of the control program based on estimation uncertainty is found

Fine-grained uncertainty relation and nonlocality of tripartite systems

The upper bound of the fine-grained uncertainty relation is different for classical physics, quantum physics and no-signaling theories with maximal nonlocality (supper quantum correlation), as was shown in the case of bipartite systems [J. Oppenheim and S. Wehner, Science 330, 1072 (2010)]. Here, we extend the fine-grained uncertainty relation to the case of tripartite systems. We show that the fine-grained uncertainty relation determines the nonlocality of tripartite systems as manifested by the Svetlichny inequality, discriminating between classical physics, quantum physics and super quantum correlations.Comment: 4 page

Entropy and Uncertainty of Squeezed Quantum Open Systems

We define the entropy S and uncertainty function of a squeezed system interacting with a thermal bath, and study how they change in time by following the evolution of the reduced density matrix in the influence functional formalism. As examples, we calculate the entropy of two exactly solvable squeezed systems: an inverted harmonic oscillator and a scalar field mode evolving in an inflationary universe. For the inverted oscillator with weak coupling to the bath, at both high and low temperatures, $S\to r$, where r is the squeeze parameter. In the de Sitter case, at high temperatures, $S\to (1-c)r$ where $c = \gamma_0/H$, $\gamma_0$ being the coupling to the bath and H the Hubble constant. These three cases confirm previous results based on more ad hoc prescriptions for calculating entropy. But at low temperatures, the de Sitter entropy $S\to (1/2-c)r$ is noticeably different. This result, obtained from a more rigorous approach, shows that factors usually ignored by the conventional approaches, i.e., the nature of the environment and the coupling strength betwen the system and the environment, are important.Comment: 36 pages, epsfig, 2 in-text figures include

Optimizing Resolution and Uncertainty in Bathymetric Sonar Systems

Bathymetric sonar systems (whether multibeam or phase-differencing sidescan) contain an inherent trade-off between resolution and uncertainty. Systems are traditionally designed with a fixed spatial resolution, and the parameter settings are optimized to minimize the uncertainty in the soundings within that constraint. By fixing the spatial resolution of the system, current generation sonars operate sub-optimally when the SNR is high, producing soundings with lower resolution than is supportable by the data, and inefficiently when the SNR is low, producing high-uncertainty soundings of little value. Here we propose fixing the sounding measurement uncertainty instead, and optimizing the resolution of the system within that uncertainty constraint. Fixing the sounding measurement uncertainty produces a swath with a variable number of bathymetric estimates per ping, in which each estimate’s spatial resolution is optimized by combining measurements only until the desired depth uncertainty is achieved. When the signal to noise ratio is sufficiently high such that the desired depth uncertainty is achieved with individual measurements, bathymetric estimates are produced at the sonar’s full resolution capability. Correspondingly, a sonar’s resolution is no-longer only considered as a property of the sonar (based on, for example, beamwidth and bandwidth,) but now incorporates geometrical aspects of the measurements and environmental factors (e.g., seafloor scattering strength). Examples are shown from both multibeam and phase- differencing sonar systems

Task Specific Uncertainty in Coordinate Measurement

Task specific uncertainty is the measurement uncertainty associated with the measurement of a specific feature using a specific measurement plan. This paper surveys techniques developed to model and estimate task specific uncertainty for coordinate measuring systems, primarily coordinate measuring machines using contacting probes. Sources of uncertainty are also reviewed

Traveller Behaviour: Decision making in an unpredictable world

This paper discusses the nature and consequences of uncertainty in transport systems. Drawing on work from a number of fields, it addresses travellers’ abilities to predict variable phenomena, their perception of uncertainty, their attitude to risk and the various strategies they might adopt in response to uncertainty. It is argued that despite the increased interest in the representation of uncertainty in transport systems, most models treat uncertainty as a purely statistical issue and ignore the psychological aspects of response to uncertainty. The principle theories and models currently used to predict travellers’ response to uncertainty are presented and number of alternative modelling approaches are outlined. It is argued that the current generation of predictive models do not provide an adequate basis for forecasting response to changes in the degree of uncertainty or for predicting the likely effect of providing additional information. A number of alternative modelling approaches are identified to deal with travellers’ acquisition of information, the definition of their choice set and their choice between the available options. The use of heuristic approaches is recommended as an alternative to more conventional probabilistic methods