Temporal and statistical information in causal structure learning

Three experiments examined children’s and adults’ abilities to use statistical and temporal information to distinguish between common cause and causal chain structures. In Experiment 1, participants were provided with conditional probability information and/or temporal information and asked to infer the causal structure of a three-variable mechanical system that operated probabilistically. Participants of all ages preferentially relied on the temporal pattern of events in their inferences, even if this conflicted with statistical information. In Experiments 2 and 3, participants observed a series of interventions on the system, which in these experiments operated deterministically. In Experiment 2, participants found it easier to use temporal pattern information than statistical information provided as a result of interventions. In Experiment 3, in which no temporal pattern information was provided, children from 6-7 years, but not younger children, were able to use intervention information to make causal chain judgments, although they had difficulty when the structure was a common cause. The findings suggest that participants, and children in particular, may find it more difficult to use statistical information than temporal pattern information because of its demands on information processing resources. However, there may also be an inherent preference for temporal information.

A Framework for Prototyping and Reasoning about Distributed Systems

A framework supporting fast prototyping as well as tuning of distributed applications is presented. The approach is based on the adoption of a formal model that is used to describe the orchestration of distributed applications. The formal model (Orc by Misra and Cook) can be used to support semi-formal reasoning about the applications at hand. The paper describes how the framework can be used to derive and evaluate alternative orchestrations of a well know parallel/distributed computation pattern; and shows how the same formal model can be used to support generation of prototypes of distributed applications skeletons directly from the application description.

Adding metadata to Orc to support reasoning about grid programs

Following earlier work demonstrating the utility of Orc as a means of specifying and reasoning about grid applications we propose the enhancement of such specifications with metadata that provide a means to extend an Orc specification with implementation oriented information. We argue that such specifications provide a useful refinement step in allowing reasoning about implementation related issues ahead of actual implementation or even prototyping. As examples, we demonstrate how such extended specifications can be used for investigating security related issues and for evaluating the cost of handling grid resource faults. The approach emphasises a semi-formal style of reasoning that makes maximum use of programmer domain knowledge and experience.

Children’s essentialist reasoning about language and race

Across four studies, we directly compared children’s essentialist reasoning about the stability of race and language throughout an individual’s lifespan. Monolingual English-speaking children were presented with a series of images of children who were either White or Black; each face was paired with a voice clip in either English or French. Participants were asked which of two adults each target child would grow up to be – one who was a ‘match’ to the target child in race but not language, and the other a ‘match’ in language but not race. Nine- to 10-year-old European American children chose the race-match, rather than the language-match. In contrast, 5–6-year-old European American children in both urban, racially diverse, and rural, racially homogeneous environments chose the language-match, even though this necessarily meant that the target child would transform racial categories. Although surprising in light of adult reasoning, these young children demonstrated an intuition about the relative stability of an individual’s language compared to her racial group membership. Yet, 5–6-year-old African American children, similar to the older European American children, chose the race-match, suggesting that membership in a racial minority group may highlight children’s reasoning about race as a stable category. Theoretical implications for our understanding of children’s categorization of human kinds are discussed.

An Extended Event Reasoning Framework for Decision Support under Uncertainty

To provide in-time reactions to a large volume of surveil- lance data, uncertainty-enabled event reasoning frameworks for CCTV and sensor based intelligent surveillance system have been integrated to model and infer events of interest. However, most of the existing works do not consider decision making under uncertainty which is important for surveillance operators. In this paper, we extend an event reasoning framework for decision support, which enables our framework to predict, rank and alarm threats from multiple heterogeneous sources.

In and out of home care decisions: The influence of confirmation bias in developing decision supportive reasoning

The aims of this study were to identify the themes Social Workers regard as important in supporting decisions to remove children from, or return them to, the care of their parents. To further elicit underlying hypotheses that are discernible in interpretation of evidence. A case study, comprising a two-part vignette with a questionnaire, recorded demographic information, child welfare attitudes and risk assessments, using scales derived from standardised instruments, was completed by 202 Social Workers in Northern Ireland. There were two manipulated variables, mother’s attitude to removal and child’s attitude to reunification2 years later. In this paper we use data derived from respondents’ qualitative comments explaining their reasoning for in and out of home care decisions. Some 60.9% of respondent’s chose the parental care option at part one, with 94% choosing to have the child remain in foster care at part two. The manipulated variables were found to have no significant statistical effect. However, three underlying hypotheses were found to underpin decisions; (a)child rescue, (b) kinship defence and (c) a hedged position on calculation of risk subject to further assessment. Reasoning strategies utilised by social workers to support their decision making suggest that they tend to selectively interpret information either positively or negatively to support pre-existing underlying hypotheses. This finding is in keeping with the literature on ‘confirmation bias.’ The research further draws attention to the need to incorporate open questions in quantitative studies, to help guard against surface reading of data, which often does not ‘speak for itself.’

Evidence reasoning for event inference in smart transport video surveillance

In this paper we present a new event recognition framework, based on the Dempster-Shafer theory of evidence, which combines the evidence from multiple atomic events detected by low-level computer vision analytics. The proposed framework employs evidential network modelling of composite events. This approach can effectively handle the uncertainty of the detected events, whilst inferring high-level events that have semantic meaning with high degrees of belief. Our scheme has been comprehensively evaluated against various scenarios that simulate passenger behaviour on public transport platforms such as buses and trains. The average accuracy rate of our method is 81% in comparison to 76% by a standard rule-based method.

Genetic Evidence for a Causal Role of Obesity in Diabetic Kidney Disease

Obesity has been posited as an independent risk factor for diabetic kidney disease (DKD), but establishing causality from observational data is problematic. We aimed to test whether obesity is causally related to DKD using Mendelian randomization, which exploits the random assortment of genes during meiosis. In 6,049 subjects with type 1 diabetes, we used a weighted genetic risk score (GRS) comprised of 32 validated BMI loci as an instrument to test the relationship of BMI with macroalbuminuria, end-stage renal disease (ESRD), or DKD defined as presence of macroalbuminuria or ESRD. We compared these results with cross-sectional and longitudinal observational associations. Longitudinal analysis demonstrated a U-shaped relationship of BMI with development of macroalbuminuria, ESRD, or DKD over time. Cross-sectional observational analysis showed no association with overall DKD, higher odds of macroalbuminuria (for every 1 kg/m(2) higher BMI, odds ratio [OR] 1.05, 95% CI 1.03-1.07, P < 0.001), and lower odds of ESRD (OR 0.95, 95% CI 0.93-0.97, P < 0.001). Mendelian randomization analysis showed a 1 kg/m(2) higher BMI conferring an increased risk in macroalbuminuria (OR 1.28, 95% CI 1.11-1.45, P = 0.001), ESRD (OR 1.43, 95% CI 1.20-1.72, P < 0.001), and DKD (OR 1.33, 95% CI 1.17-1.51, P < 0.001). Our results provide genetic evidence for a causal link between obesity and DKD in type 1 diabetes. As obesity prevalence rises, this finding predicts an increase in DKD prevalence unless intervention should occur.