Learning First-Order Definitions of Functions

First-order learning involves finding a clause-form definition of a relation from examples of the relation and relevant background information. In this paper, a particular first-order learning system is modified to customize it for finding definitions of functional relations. This restriction leads to faster learning times and, in some cases, to definitions that have higher predictive accuracy. Other first-order learning systems might benefit from similar specialization.Comment: See http://www.jair.org/ for any accompanying file

Discovering Regression Rules with Ant Colony Optimization

The majority of Ant Colony Optimization (ACO) algorithms for data mining have dealt with classification or clustering problems. Regression remains an unexplored research area to the best of our knowledge. This paper proposes a new ACO algorithm that generates regression rules for data mining applications. The new algorithm combines components from an existing deterministic (greedy) separate and conquer algorithm—employing the same quality metrics and continuous attribute processing techniques—allowing a comparison of the two. The new algorithm has been shown to decrease the relative root mean square error when compared to the greedy algorithm. Additionally a different approach to handling continuous attributes was investigated showing further improvements were possible

Stone tools and the linguistic capabilities of earlier hominids

The evolution of human manipulative abilities may be clearly linked to the evolution of speech motor control Both creativity and complexity in vocal and manipulative gestures may be closely linked to a single dimension of brain evolution — the evolution of absolute brain size. Inferring the linguistic capabilities of earlier hominids from their lithic artefacts, however, required us to take account of domain-specific constraints on manipulative skill In this article we report on a pilot flint-knapping experiment designed to identify such constraints ‘in action’

Unitary groups over local rings

Structural properties of unitary groups over local, not necessarily commutative, rings are developed, with applications to the computation of the orders of these groups (when finite) and to the degrees of the irreducible constituents of the Weil representation of a unitary group associated to a ramified extension of finite local rings

SDaN: Software Defined Adaptive Networking - IoT and beyond

In this position paper, I present my vision on how enhancing the interaction between devices in an Internet of Things (IoT) network and the mechanisms of Software Defined Networking (SDN) can not only improve the efficiency of wirelessly transmitted data but can strengthen the viability and manageability of devices in an IoT network and beyond. By expanding the composition of SDN to encompass not only the existing North (controller API), South (device API), East and West interfaces (distributed controller(s) API) – viewed as an X-/Y-axis, but also an holistic adaptive Z-axis, which mandates a higher layer abstraction of the root APIs irrespective of the underlying architecture. This adaptive Z-axis improves the global view by offering an abstracted view of the network control and management for all objects in the network. In this proposal all interfaces, irrespective of axis, can be viewed as a single abstraction, by which inter-operative function calls can be leveraged adaptively between the device(s) and the network(s). By leveraging these additional constructs, I believe SDN can improve the capabilities and efficiency of IoT networks and beyond

Addressing Youth Perceptions of Harm in Marijuana Prevention Programming

The inverse relationship between perception of harm and substance use is clearly supported by decades of research – youth are less likely to engage in substance use when it is seen as harmful. However, despite strong theoretical and practical reasons to focus on perception of harm as a change-producer in prevention programming, little is known about what is effective in impacting perception of harm for youth marijuana use. To investigate the impact of existing prevention efforts designed to influence youth perception of harm and, consequently, youth marijuana use, we reviewed seven privately- or federally-funded online registries (e.g., Blueprints for Healthy Youth Development, Substance Abuse and Mental Health Administration’s National Registry of Evidence Based Programs and Practices) to identify evidence-based programs with marijuana-related outcomes for youth. We found 36 registry-identified programs with demonstrated impact on youth marijuana use. Although many of these programs may have actively or passively sought to alter perception of harm, only ten measured marijuana- or drug-related perception of harm as an intermediate outcome. Drawing on the commonalities of evidence-based programs with significant impacts on youth marijuana perception of harm, as well as lessons learned from other health behavior change efforts, we recommend best practices to provide state and local decision-makers with information on altering youth perception of harm for marijuana and on evaluating the impact of these efforts

Improved Use of Continuous Attributes in C4.5

A reported weakness of C4.5 in domains with continuous attributes is addressed by modifying the formation and evaluation of tests on continuous attributes. An MDL-inspired penalty is applied to such tests, eliminating some of them from consideration and altering the relative desirability of all tests. Empirical trials show that the modifications lead to smaller decision trees with higher predictive accuracies. Results also confirm that a new version of C4.5 incorporating these changes is superior to recent approaches that use global discretization and that construct small trees with multi-interval splits.Comment: See http://www.jair.org/ for any accompanying file