Autonomous Agents for Business Process Management

Traditional approaches to managing business processes are often inadequate for large-scale organisation-wide, dynamic settings. However, since Internet and Intranet technologies have become widespread, an increasing number of business processes exhibit these properties. Therefore, a new approach is needed. To this end, we describe the motivation, conceptualization, design, and implementation of a novel agent-based business process management system. The key advance of our system is that responsibility for enacting various components of the business process is delegated to a number of autonomous problem solving agents. To enact their role, these agents typically interact and negotiate with other agents in order to coordinate their actions and to buy in the services they require. This approach leads to a system that is significantly more agile and robust than its traditional counterparts. To help demonstrate these benefits, a companion paper describes the application of our system to a real-world problem faced by British Telecom

Implementing a Business Process Management System Using ADEPT: A Real-World Case Study

This article describes how the agent-based design of ADEPT (advanced decision environment for processed tasks) and implementation philosophy was used to prototype a business process management system for a real-world application. The application illustrated is based on the British Telecom (BT) business process of providing a quote to a customer for installing a network to deliver a specified type of telecommunication service. Particular emphasis is placed upon the techniques developed for specifying services, allowing heterogeneous information models to interoperate, allowing rich and flexible interagent negotiation to occur, and on the issues related to interfacing agent-based systems and humans. This article builds upon the companion article (Applied Artificial Intelligence Vol.14, no 2, pgs. 145-189) that provides details of the rationale and design of the ADEPT technology deployed in this application

Effectiveness of group-based self-management education for individuals with Type 2 diabetes:A systematic review with meta-analyses and meta-regression

Aims: Patient education for the management of Type 2 diabetes can be delivered in various forms, with the goal of promoting and supporting positive self-management behaviours. This systematic review aimed to determine the effectiveness of group-based interventions compared with individual interventions or usual care for improving clinical, lifestyle and psychosocial outcomes in people with Type 2 diabetes. Methods: Six electronic databases were searched. Group-based education programmes for adults with Type 2 diabetes that measured glycated haemoglobin (HbA1c) and followed participants for ≥ 6 months were included. The primary outcome was HbA1c, and secondary outcomes included fasting blood glucose, weight, body mass index, waist circumference, blood pressure, blood lipid profiles, diabetes knowledge and self-efficacy. Results: Fifty-three publications describing 47 studies were included (n = 8533 participants). Greater reductions in HbA1c occurred in group-based education compared with controls at 6–10 months [n = 30 studies; mean difference (MD) = 3 mmol/mol (0.3%); 95% confidence interval (CI): −0.48, −0.15; P = 0.0002], 12–14 months [n = 27 studies; MD = 4 mmol/mol (0.3%); 95% CI: −0.49, −0.17; P < 0.0001], 18 months [n = 3 studies; MD = 8 mmol/mol (0.7%); 95% CI: −1.26, −0.18; P = 0.009] and 36–48 months [n = 5 studies; MD = 10 mmol/mol (0.9%); 95% CI: −1.52, −0.34; P = 0.002], but not at 24 months. Outcomes also favoured group-based education for fasting blood glucose, body weight, waist circumference, triglyceride levels and diabetes knowledge, but not at all time points. Interventions facilitated by a single discipline, multidisciplinary teams or health professionals with peer supporters resulted in improved outcomes in HbA1c when compared with peer-led interventions. Conclusions: Group-based education interventions are more effective than usual care, waiting list control and individual education at improving clinical, lifestyle and psychosocial outcomes in people with Type 2 diabetes.No Full Tex

Exposure to maternal versus paternal partner violence, PTSD and aggression in adolescent girls and boys

Adolescents who witness interparental violence (IPV) are at increased risk for perpetrating aggressive acts. They are also at risk for post-traumatic stress disorder (PTSD). In this study, we examined the relation between exposure to maternal vs. paternal physical IPV and adolescent girls\u27 and boys\u27 aggressive behavior toward mothers, fathers, friends, and romantic partners. We also assessed the influence of PTSD (as assessed by the Diagnostic Interview for Children and Adolescents-IV (DICA-IV)) on the relation between exposure to IPV and aggressive behavior. Participants were 63 girls and 49 boys, ages 13-18, consecutively admitted to a youth correctional facility or assessment facility designated to serve aggressive and delinquent youth. Structural equation modeling was used to estimate unique relations between exposure to maternal vs. paternal IPV and youth aggression in relationships. Girls who observed their mothers\u27 aggressive behavior toward partners were significantly more aggressive toward friends. Similarly, boys who witnessed their fathers\u27 aggression were significantly more aggressive toward friends. Adolescent girls and boys who observed aggression by mothers toward partners reported significantly higher levels of aggression toward their romantic partners. Approximately one third of our sample met PTSD criteria; the relation between exposure to parental IPV and aggression was stronger for individuals who met criteria for PTSD. The implications of understanding the relations between parents\u27 and their daughters\u27 and sons\u27 use of aggression are discussed within the context of providing support for families in breaking intergenerational patterns of violence and aggression

A latent variable modeling approach to identifying subtypes of serious and violent female offenders

Females have recently become an important population in research related to serious and violent juvenile offending. Although a small body of research exists on girls in the deep end of the system, very few studies have examined the degree of heterogeneity within high-risk female samples. This study applied latent class analysis (LCA) to identify subgroups of female juvenile offenders based on their self-report of offending profiles (N=133). Results supported a three-class solution with subgroups characterized by patterns of \u27violent and delinquent\u27, \u27delinquency only\u27, and \u27low\u27 offending patterns. The LCA solution was replicated in an independent sample of high-risk females. The \u27violent and delinquent\u27 class was characterized by significantly higher rates of DSM-IV diagnoses for internalizing disorders, affect dysregulation, exposure to violence (within the home, school and neighborhood), and familial histories of criminality. Implications for future research, policy and clinical practice are discussed

POLARIS: A 30-meter probabilistic soil series map of the contiguous United States

A newcomplete map of soil series probabilities has been produced for the contiguous United States at a 30mspatial resolution. This innovative database, named POLARIS, is constructed using available high-resolution geospatial environmental data and a state-of-the-art machine learning algorithm (DSMART-HPC) to remap the Soil Survey Geographic (SSURGO) database. This 9 billion grid cell database is possible using available high performance computing resources. POLARIS provides a spatially continuous, internally consistent, quantitative prediction of soil series. It offers potential solutions to the primary weaknesses in SSURGO: 1) unmapped areas are gap-filled using survey data from the surrounding regions, 2) the artificial discontinuities at political boundaries are removed, and 3) the use of high resolution environmental covariate data leads to a spatial disaggregation of the coarse polygons. The geospatial environmental covariates that have the largest role in assembling POLARIS over the contiguous United States (CONUS) are fine-scale (30 m) elevation data and coarse-scale (~2 km) estimates of the geographic distribution of uranium, thorium, and potassium. A preliminary validation of POLARIS using the NRCS National Soil Information System (NASIS) database shows variable performance over CONUS. In general, the best performance is obtained at grid cells where DSMART-HPC is most able to reduce the chance of misclassification. The important role of environmental covariates in limiting prediction uncertainty suggests including additional covariates is pivotal to improving POLARIS\u27 accuracy. This database has the potential to improve the modeling of biogeochemical, water, and energy cycles in environmental models; enhance availability of data for precision agriculture; and assist hydrologic monitoring and forecasting to ensure food and water security

Association between genetic and socioenvironmental risk for schizophrenia during upbringing in a UK longitudinal cohort

BACKGROUND: Associations of socioenvironmental features like urbanicity and neighborhood deprivation with psychosis are well-established. An enduring question, however, is whether these associations are causal. Genetic confounding could occur due to downward mobility of individuals at high genetic risk for psychiatric problems into disadvantaged environments. METHODS: We examined correlations of five indices of genetic risk [polygenic risk scores (PRS) for schizophrenia and depression, maternal psychotic symptoms, family psychiatric history, and zygosity-based latent genetic risk] with multiple area-, neighborhood-, and family-level risks during upbringing. Data were from the Environmental Risk (E-Risk) Longitudinal Twin Study, a nationally-representative cohort of 2232 British twins born in 1994–1995 and followed to age 18 (93% retention). Socioenvironmental risks included urbanicity, air pollution, neighborhood deprivation, neighborhood crime, neighborhood disorder, social cohesion, residential mobility, family poverty, and a cumulative environmental risk scale. At age 18, participants were privately interviewed about psychotic experiences. RESULTS: Higher genetic risk on all indices was associated with riskier environments during upbringing. For example, participants with higher schizophrenia PRS (OR = 1.19, 95% CI = 1.06–1.33), depression PRS (OR = 1.20, 95% CI = 1.08–1.34), family history (OR = 1.25, 95% CI = 1.11–1.40), and latent genetic risk (OR = 1.21, 95% CI = 1.07–1.38) had accumulated more socioenvironmental risks for schizophrenia by age 18. However, associations between socioenvironmental risks and psychotic experiences mostly remained significant after covariate adjustment for genetic risk. CONCLUSION: Genetic risk is correlated with socioenvironmental risk for schizophrenia during upbringing, but the associations between socioenvironmental risk and adolescent psychotic experiences appear, at present, to exist above and beyond this gene-environment correlation

Language and social/emotional problems identified at a universal developmental assessment at 30 months

Non peer reviewedPublisher PD

Novice drivers’ individual trajectories of driver behavior over the first three years of driving

Identifying the changes in driving behavior that underlie the decrease in crash risk over the first few months of driving is key to efforts to reduce injury and fatality risk in novice drivers. This study represented a secondary data analysis of 1148 drivers who participated in the UK Cohort II study. The Driver Behavior Questionnaire was completed at 6 months and 1, 2 and 3 years after licensure. Linear latent growth models indicated significant increases across development in all four dimensions of aberrant driving behavior under scrutiny: aggressive violations, ordinary violations, errors and slips. Unconditional and conditional latent growth class analyses showed that the observed heterogeneity in individual trajectories was explained by the presence of multiple homogeneous groups of drivers, each exhibiting specific trajectories of aberrant driver behavior. Initial levels of aberrant driver behavior were important in identifying sub-groups of drivers. All classes showed positive slopes; there was no evidence of a group of drivers whose aberrant behavior decreased over time that might explain the decrease in crash involvement observed over this period. Male gender and younger age predicted membership of trajectories with higher levels of aberrant behavior. These findings highlight the importance of early intervention for improving road safety. We discuss the implications of our findings for understanding the behavioral underpinnings of the decrease in crash involvement observed in the early months of driving