Imprecise probabilistic query answering using measures of ignorance and degree of satisfaction

In conditional probabilistic logic programming, given a query, the two most common forms for answering the query are either a probability interval or a precise probability obtained by using the maximum entropy principle. The former can be noninformative (e.g.,interval [0; 1]) and the reliability of the latter is questionable when the priori knowledge isimprecise. To address this problem, in this paper, we propose some methods to quantitativelymeasure if a probability interval or a single probability is sufficient for answering a query. We first propose an approach to measuring the ignorance of a probabilistic logic program with respect to a query. The measure of ignorance (w.r.t. a query) reflects howreliable a precise probability for the query can be and a high value of ignorance suggests that a single probability is not suitable for the query. We then propose a method to measure the probability that the exact probability of a query falls in a given interval, e.g., a second order probability. We call it the degree of satisfaction. If the degree of satisfaction is highenough w.r.t. the query, then the given interval can be accepted as the answer to the query. We also prove our measures satisfy many properties and we use a case study to demonstrate the significance of the measures. © Springer Science+Business Media B.V. 2012

The prospective effects of workplace violence on physicians' job satisfaction and turnover intentions: the buffering effect of job control

Background: Health care professionals, including physicians, are at high risk of encountering workplace violence. At the same time physician turnover is an increasing problem that threatens the functioning of the health care sector worldwide. The present study examined the prospective associations of work-related physical violence and bullying with physicians’ turnover intentions and job satisfaction. In addition, we tested whether job control would modify these associations.

Methods: The present study was a 4-year longitudinal survey study, with data gathered in 2006 and 2010.The present sample included 1515 (61% women) Finnish physicians aged 25–63 years at baseline. Analyses of covariance (ANCOVA) were conducted while adjusting for gender, age, baseline levels, specialisation status, and employment sector.

Results: The results of covariance analyses showed that physical violence led to increased physician turnover intentions and that both bullying and physical violence led to reduced physician job satisfaction even after adjustments. We also found that opportunities for job control were able to alleviate the increase in turnover intentions resulting from bullying.

Conclusions: Our results suggest that workplace violence is an extensive problem in the health care sector and may lead to increased turnover and job dissatisfaction. Thus, health care organisations should approach this problem through different means, for example, by giving health care employees more opportunities to control their own work.

The List_Tree - an innovative solution to customer portfolio representation

The scale of BT's operations necessitates the use of very large scale computing systems, and the storage and management of large volumes of data. Customer product portfolios are an important form of data which can be difficult to store in a space efficient way. The difficulties arise from the inherently structured form of product portfolios, and the fact that they change over time as customers add or remove products. This paper introduces a new data-modelling abstraction called the List_Tree. It has been designed specifically to support the efficient storage and manipulation of customer product portfolios, but may also prove useful in other applications with similar general requirements.