No time for compliance

In the past few years several business process compliance framework based on temporal logic have been proposed. In this paper we investigate whether the use of temporal logic is suitable for the task at hand: namely to check whether the specifications of a business process are compatible with the formalisation of the norms regulating the business process. We provide an example inspired by real life norms where the use of linear temporal logic produces a result that is not compatible with the legal understanding of the norms in the example.

Modelling the activation of words in human memory : the spreading activation, spooky-activation-at-a-distance and the entanglement models compared

Modelling how a word is activated in human memory is an important requirement for determining the probability of recall of a word in an extra-list cueing experiment. The spreading activation, spooky-action-at-a-distance and entanglement models have all been used to model the activation of a word. Recently a hypothesis was put forward that the mean activation levels of the respective models are as follows: Spreading � Entanglment � Spooking-action-at-a-distance This article investigates this hypothesis by means of a substantial empirical analysis of each model using the University of South Florida word association, rhyme and word norms.

Predicting Australian adults' sun-safe behaviour : examining the role of personal and social norms

Objectives To address the scarcity of comprehensive, theory-based research in the Australian context, this study, using a theory of planned behaviour (TPB) framework, investigated the role of personal and social norms to identify the key predictors of adult Australians' sun-safe intentions and behaviour. Design The study used a prospective design with two waves of data collection, 1 week apart. Methods Participants were 816 adults (48.2% men) aged between 18 and 88 years recruited from urban, regional, and rural areas of Australia. At baseline, participants completed a questionnaire assessing the standard TPB predictors (attitude, subjective norm, and perceived behavioural control [PBC]), past behaviour, behavioural intention, and additional measures of group norm for the referent groups of friends and family, image norm, personal norm, personal choice/responsibility, and Australian identity. Seventy-one per cent of the participants (n = 577) reported on their sun-safe behaviour in the subsequent week. Results Via path modelling, past behaviour, attitude, group norm (friends), personal norm, and personal choice/responsibility emerged as independent predictors of intentions which, in turn, predicted sun-safe behaviour prospectively. Past behaviour, but not PBC, had direct effects on sun-safe behaviour. The model explained 61.6% and 43.9% of the variance in intention and behaviour, respectively. Conclusions This study provides support for the use of a comprehensive theoretical decision-making model to explain Australian adults' sun-safe intentions and behaviours and identifies viable targets for health-promoting messages in this high-risk context.

A methodology for extracting legal norms from regulatory documents

We present a methodology to extract legal norms from regulatory documents for their formalisation and later compliance checking. The need for the methodology is motivated from the shortcomings of existing approaches where the rule type and process aspects relevant to the rules are largely overlook. The methodology incorporates the well–known IF. . . THEN structure extended with the process aspect and rule type, and guides how to properly extract the conditions and logical structure of the legal rules for reasoning and modelling of obligations for compliance checking.

Modelling Cued-Target Recall using Quantum Inspired Models of Target Activation

This article presents and evaluates Quantum Inspired models of Target Activation using Cued-Target Recall Memory Modelling over multiple sources of Free Association data. Two components were evaluated: Whether Quantum Inspired models of Target Activation would provide a better framework than their classical psychological counterparts and how robust these models are across the different sources of Free Association data. In previous work, a formal model of cued-target recall did not exist and as such Target Activation was unable to be assessed directly. Further to that, the data source used was suspected of suffering from temporal and geographical bias. As a consequence, Target Activation was measured against cued-target recall data as an approximation of performance. Since then, a formal model of cued-target recall (PIER3) has been developed [10] with alternative sources of data also becoming available. This allowed us to directly model target activation in cued-target recall with human cued-target recall pairs and use multiply sources of Free Association Data. Featural Characteristics known to be important to Target Activation were measured for each of the data sources to identify any major differences that may explain variations in performance for each of the models. Each of the activation models were used in the PIER3 memory model for each of the data sources and was benchmarked against cued-target recall pairs provided by the University of South Florida (USF). Two methods where used to evaluate performance. The first involved measuring the divergence between the sets of results using the Kullback Leibler (KL) divergence with the second utilizing a previous statistical analysis of the errors [9]. Of the three sources of data, two were sourced from human subjects being the USF Free Association Norms and the University of Leuven (UL) Free Association Networks. The third was sourced from a new method put forward by Galea and Bruza, 2015 in which pseudo Free Association Networks (Corpus Based Association Networks - CANs) are built using co-occurrence statistics on large text corpus. It was found that the Quantum Inspired Models of Target Activation not only outperformed the classical psychological model but was more robust across a variety of data sources.