Implementing Network Protocols as Distributed Logic Programs

Declarative networking [2, 4, 3, 1] is an application of database query-language and processing techniques to the domain of networking. Declarative networking is based on the observation that network protocols deal at their core with computing and maintaining distributed state (e.g., routes, sessions, performance statistics) according to basic information locally available at each node (e.g., neighbor tables, link measurements, local clocks) while enforcing constraints such as local routing policies. Recursive query languages studied in the deductive database literature [6] are a natural fit for expressing the relationship between base data, derived data, and the associated constraints. Simple extensions to these languages and their implementations enable the natural expression and efficient execution of network protocols. Declarative networking aims to accelerate the process of specifying, implementing, experimenting with and evolving designs for network architectures. Declarative networking can reduce program sizes of distributed protocols by orders of magnitude relative to traditional approaches. In addition to serving as a platform for rapid prototyping of network protocols, declarative networking also open up opportunities for automatic protocol optimization and hybridization, program checking and debugging. This paper presents an introduction to declarative networking using a simple routing protocol example. For more details on declarative networking related projects, refer to the NetDB@Penn website [5], and the RapidNet [7] declarative networking engine

Assessing schematic knowledge of introductory probability theory

[Abstract]: The ability to identify schematic knowledge is an important goal for both assessment and instruction. In the current paper, schematic knowledge of statistical probability theory is explored from the declarative-procedural framework using multiple methods of assessment. A sample of 90 undergraduate introductory statistics students was required to classify 10 pairs of probability problems as similar or different; to identify whether 15 problems contained sufficient, irrelevant, or missing information (text-edit); and to solve 10 additional problems. The complexity of the schema on which the problems were based was also manipulated. Detailed analyses compared text-editing and solution accuracy as a function of text-editing category and schema complexity. Results showed that text-editing tends to be easier than solution and differentially sensitive to schema complexity. While text-editing and classification were correlated with solution, only text-editing problems with missing information uniquely predicted success. In light of previous research these results suggest that text-editing is suitable for supplementing the assessment of schematic knowledge in development

An examination of the mediating role of salt knowledge and beliefs on the relationship between socio-demographic factors and discretionary salt use: a cross-sectional study

Background Discretionary salt use varies according to socio-demographic factors. However, it is unknown whether salt knowledge and beliefs mediate this relationship. This study examined the direct and indirect effect of socio-demographic factors on salt knowledge and discretionary salt use in a sample of 530 Australian adults.Methods An internet based cross-sectional survey was used to collect data for this study. Participants completed an online questionnaire which assessed their salt knowledge, beliefs and salt use behaviour. Mplus was used to conduct structural equation modelling to estimate direct and indirect effects.Results The mean age of the participants was 49.2 years, and about a third had tertiary education. Discretionary salt use was inversely related to age (r=-0.11; p&lt;0.05), and declarative salt knowledge (knowledge of factual information) scores (r = -0.17; p&lt;0.01), but was positively correlated with misconceptions about salt (r = 0.09; p&lt;0.05) and beliefs about the taste of salt (r = 0.51; p&lt;0.001). Structural equation modelling showed age, education and gender were indirectly associated with the use of discretionary salt through three mediating pathways; declarative salt knowledge, misconceptions about salt and salt taste beliefs.Conclusions Inequalities observed between socio-demographic groups in their use of discretionary salt use can potentially be reduced through targeted salt knowledge and awareness campaigns.<br /

Explicit learning in ACT-R

A popular distinction in the learning literature is the distinction between implicit and explicit learning. Although many studies elaborate on the nature of implicit learning, little attention is left for explicit learning. The unintentional aspect of implicit learning corresponds well to the mechanistic view of learning employed in architectures of cognition. But how to account for deliberate, intentional, explicit learning? This chapter argues that explicit learning can be explained by strategies that exploit implicit learning mechanisms. This idea is explored and modelled using the ACT-R theory (Anderson, 1993). An explicit strategy for learning facts in ACT-R’s declarative memory is rehearsal, a strategy that uses ACT-R’s activation learning mechanisms to gain deliberate control over what is learned. In the same sense, strategies for explicit procedural learning are proposed. Procedural learning in ACT-R involves generalisation of examples. Explicit learning rules can create and manipulate these examples. An example of these explicit rules will be discussed. These rules are general enough to be able to model the learning of three different tasks. Furthermore, the last of these models can explain the difference between adults and children in the discrimination-shift task

Investigation of the use of navigation tools in web-based learning: A data mining approach

Web-based learning is widespread in educational settings. The popularity of Web-based learning is in great measure because of its flexibility. Multiple navigation tools provided some of this flexibility. Different navigation tools offer different functions. Therefore, it is important to understand how the navigation tools are used by learners with different backgrounds, knowledge, and skills. This article presents two empirical studies in which data-mining approaches were used to analyze learners' navigation behavior. The results indicate that prior knowledge and subject content are two potential factors influencing the use of navigation tools. In addition, the lack of appropriate use of navigation tools may adversely influence learning performance. The results have been integrated into a model that can help designers develop Web-based learning programs and other Web-based applications that can be tailored to learners' needs

Declarative Modeling and Bayesian Inference of Dark Matter Halos

Probabilistic programming allows specification of probabilistic models in a declarative manner. Recently, several new software systems and languages for probabilistic programming have been developed on the basis of newly developed and improved methods for approximate inference in probabilistic models. In this contribution a probabilistic model for an idealized dark matter localization problem is described. We first derive the probabilistic model for the inference of dark matter locations and masses, and then show how this model can be implemented using BUGS and Infer.NET, two software systems for probabilistic programming. Finally, the different capabilities of both systems are discussed. The presented dark matter model includes mainly non-conjugate factors, thus, it is difficult to implement this model with Infer.NET.Comment: Presented at the Workshop "Intelligent Information Processing", EUROCAST2013. To appear in selected papers of Computer Aided Systems Theory - EUROCAST 2013; Volumes Editors: Roberto Moreno-D\'iaz, Franz R. Pichler, Alexis Quesada-Arencibia; LNCS Springe

Conformance Checking Based on Multi-Perspective Declarative Process Models

Process mining is a family of techniques that aim at analyzing business process execution data recorded in event logs. Conformance checking is a branch of this discipline embracing approaches for verifying whether the behavior of a process, as recorded in a log, is in line with some expected behaviors provided in the form of a process model. The majority of these approaches require the input process model to be procedural (e.g., a Petri net). However, in turbulent environments, characterized by high variability, the process behavior is less stable and predictable. In these environments, procedural process models are less suitable to describe a business process. Declarative specifications, working in an open world assumption, allow the modeler to express several possible execution paths as a compact set of constraints. Any process execution that does not contradict these constraints is allowed. One of the open challenges in the context of conformance checking with declarative models is the capability of supporting multi-perspective specifications. In this paper, we close this gap by providing a framework for conformance checking based on MP-Declare, a multi-perspective version of the declarative process modeling language Declare. The approach has been implemented in the process mining tool ProM and has been experimented in three real life case studies