Situation awareness and ability in coalitions

This paper proposes a discussion on the formal links between the Situation Calculus and the semantics of interpreted systems as far as they relate to Higher-Level Information Fusion tasks. Among these tasks Situation Analysis require to be able to reason about the decision processes of coalitions. Indeed in higher levels of information fusion, one not only need to know that a certain proposition is true (or that it has a certain numerical measure attached), but rather needs to model the circumstances under which this validity holds as well as agents' properties and constraints. In a previous paper the authors have proposed to use the Interpreted System semantics as a potential candidate for the unification of all levels of information fusion. In the present work we show how the proposed framework allow to bind reasoning about courses of action and Situation Awareness. We propose in this paper a (1) model of coalition, (2) a model of ability in the situation calculus language and (3) a model of situation awareness in the interpreted systems semantics. Combining the advantages of both Situation Calculus and the Interpreted Systems semantics, we show how the Situation Calculus can be framed into the Interpreted Systems semantics. We illustrate on the example of RAP compilation in a coalition context, how ability and situation awareness interact and what benefit is gained. Finally, we conclude this study with a discussion on possible future works

An investigation of the line of sight towards QSO PKS 0237-233

We present a detailed analysis of absorption systems along the line of sight towards QSO PKS 0237-233 using a high resolution spectrum of signal-to-noise ratio (SNR) ~ 60-80 obtained with the Ultraviolet and Visual Echelle Spectrograph mounted on the Very Large Telescope. This line of sight is known to show a remarkable overdensity of CIV systems that has been interpreted as revealing the presence of a supercluster of galaxies. A detailed analysis of each of these absorption systems is presented. In particular, for the z_abs = 1.6359 (with two components of logN(HI) = 18.45, 19.05) and z_abs = 1.6720 (logN(H I) = 19.78) sub-Damped Ly-alpha systems (sub-DLAs), we measure accurate abundances (resp. [O/H] = -1.63(0.07) and [Zn/H] = - 0.57(0.05) relative to solar). While the depletion of refractory elements onto dust grains in both sub-DLAs is not noteworthy, photoionization models show that ionization effects are important in a part of the absorbing gas of the sub-DLA at z_abs = 1.6359 (HI is 95 percent ionized) and in part of the gas of the sub-DLA at z_abs = 1.6359. The CIV clustering properties along the line of sight is studied in order to investigate the nature of the observed overdensity. We conclude that despite the unusually high number of CIV systems detected along the line of sight, there is no compelling evidence for the presence of a single unusual overdensity and that the situation is consistent with chance coincidence.Comment: Accepted for publication in MNRAS. 23 pages, 16 figures, 12 table

The statistical significance of the superhump signal in U Gem

Although its well determined mass ratio of q=\Msec/\Mwd=0.357\pm0.007 should avoid superoutbursts according to the thermal tidal instability model, the prototypical dwarf nova U Gem experienced in 1985 an extraordinary long outburst resembling very much superoutbursts observed in SU UMa systems. Recently, the situation for the model became even worse as superhump detections have been reported for the 1985 outburst of U Gem. The superhump signal is noisy and the evidence provided by simple periodograms seems to be weak. Therefore and because of the importance for our understanding of superoutbursts and superhumps, we determine the statistical significance of the recently published detection of superhumps in the AAVSO light curve of the famous long 1985 outburst of U Gem. Using Lomb-Scargle periodograms, analysis of variance (AoV), and Monte-Carlo methods we analyse the 160 visual magnitudes obtained by the AAVSO during the outburst and relate our analyse to previous superhump detections. The 160 data points of the outburst alone do not contain a statistically significant period. However, using additionally the characteristics of superhumps detected previously in other SU UMa systems and searching only for signals that are consistent with these, we derive a $2\sigma$ significance for the superhump signal. The alleged appearance of an additional superhump at the end of the outbursts appears to be statistically insignificant. Although of weak statistical significance, the superhump signal of the long 1985 outburst of U Gem can be interpreted as further indication for the SU UMa nature of this outburst. This further contradicts the tidal instability model as the explanation for the superhump phenomenon.Comment: 7 pages, 7 figures, accepted for publication in A&

Big Data Risk Assessment the 21st Century approach to safety science

Safety Science has been developed over time with notable models in the early 20th Century such as Heinrich’s iceberg model and the Swiss cheese model. Common techniques such fault tree and event tree analyses, HAZOP analysis and bow-ties construction are widely used within industry. These techniques are based on the concept that failures of a system can be caused by deviations or individual faults within a system, combinations of latent failures, or even where each part of a complex system is operating within normal bounds but a combined effect creates a hazardous situation. In this era of Big Data, systems are becoming increasingly complex, producing such a large quantity of data related to safety that cannot be meaningfully analysed by humans to make decisions or uncover complex trends that may indicate the presence of hazards. More subtle and automated techniques for mining these data are required to provide a better understanding of our systems and the environment within which they operate, and insights to hazards that may not otherwise be identified. Big Data Risk Analysis (BDRA) is a suite of techniques being researched to identify the use of non-traditional techniques from big data sources to predict safety risk. This paper describes early trials of BDRA that have been conducted on railway signal information and text-based reports of railway safety near misses and the ongoing research that is looking at combining various data sources to uncover obscured trends that cannot be identified by considering each source individually. The paper also discusses how visual analytics may be a key tool in analysing Big Data to support knowledge elicitation and decision-making, as well as providing information in a form that can be readily interpreted by a variety of audiences

Visual analysis of sensor logs in smart spaces: Activities vs. situations

Models of human habits in smart spaces can be expressed by using a multitude of representations whose readability influences the possibility of being validated by human experts. Our research is focused on developing a visual analysis pipeline (service) that allows, starting from the sensor log of a smart space, to graphically visualize human habits. The basic assumption is to apply techniques borrowed from the area of business process automation and mining on a version of the sensor log preprocessed in order to translate raw sensor measurements into human actions. The proposed pipeline is employed to automatically extract models to be reused for ambient intelligence. In this paper, we present an user evaluation aimed at demonstrating the effectiveness of the approach, by comparing it wrt. a relevant state-of-the-art visual tool, namely SITUVIS

Shape interpretation with design computing

How information is interpreted has significant impact on how it can be used. This is particularly important in design where information from a wide variety of sources is used in a wide variety of contexts and in a wide variety of ways. This paper is concerned with the information that is created, modified and analysed during design processes, specifically with the information that is represented in shapes. It investigates how design computing seeks to support these processes, and the difficulties that arise when it is necessary to consider alternative interpretations of shape. The aim is to establish the problem of shape interpretation as a general challenge for research in design computing, rather than a difficulty that is to be overcome within specific processes. Shape interpretations are common characteristics of several areas of enquiry in design computing. This paper reviews these, brings an integrated perspective and draws conclusions about how this underlying process can be supported