We present the design and deployment of a physical computing platform developed for a crossdisciplinary introduction to biology and computer science. Using the accessible Arduino interface as its foundation, students instantiate increasingly nuanced physical interactions with the environment. Biological and computational ideas receive equal attention through three layered projects that span from circuit design through the co-evolution of predator-prey robot behaviors. The low-overhead platform presented here scales to support sophisticated projects at surprisingly modest time-and-money costs

When searching a knowledge repository such as Wikipedia or the Internet, the user doesn’t always know what they are looking for. Indeed, it is often the case that a user wishes to find information about a concept that was completely unknown to them prior to the search. In this paper we describe C-Link, which provides the user with a method for searching for unknown concepts which lie between two known concepts. C-Link does this by modeling the knowledge repository as a weighted, directed graph where nodes are concepts and arc weights give the degree of “relatedness” between concepts. An experimental study was undertaken with 59 participants to investigate the performance of C-Link compared to standard search approaches. Statistical analysis of the results shows great potential for C-Link as a search tool.

For autonomous systems such as unmanned aerial vehicles tosuccessfully perform complex missions, a great deal of embedded reasoning is required at varying levels of abstraction. In order to make use of diverse reasoning modules in such systems, issues ofintegration such as sensor data flow and information flow between such modules has to be taken into account. The DyKnow framework is a tool with a formal basis that pragmatically deals with many of the architectural issues which arise in such systems. This includes a systematic stream-based method for handling the sense-reasoning gap,caused by the wide difference in abstraction levels between the noisy data generally available from sensors and the symbolic, semantically meaningful information required by many high-level reasoning modules. DyKnow has proven to be quite robust and widely applicable to different aspects of hybrid software architectures forrobotics. In this paper, we describe the DyKnow framework and show how it is integrated and used in unmanned aerial vehicle systems developed in our group. In particular, we focus on issues pertaining to the sense-reasoning gap and the symbol grounding problem and the use of DyKnow as a means of generating semantic structures representing situational awareness for such systems. We also discuss the use of DyKnow in the context of automated planning, in particular execution monitoring.

In this paper we describe the production and consumption of linked data in the scenario of the Italian news agency ANSA portal. The goal of the use-case is to provide viewers of a news item with background information and links to related news articles contained on the portal. This information enrichment process is entity-based: ANSA news archive is analyzed using Name Entity Recognition, and each detected entity is annotated with a unique identifier. These identifiers are obtained using the Entity Name Server developed within the scope of the OKKAM European project. Subsequently the news are published on the portal using RDFa and linked to a semantic search engine that provides background information harvested from sources such as DBpedia and links to additional news sources. The presented project has the potential to contribute to Linked Data by creating and publishing a large quantity of entities and assertions about them coming from the ANSA news archive.

Although the various VA methods do Challenges for Global Health (Varmus et al. 2003) have not predict causes of deaths with vague symptoms as helped to reinforce the need for evidence-based global accurately as laboratory diagnostics can, verbal autopsy health priorities. Accurate health metrics and improved can predict causes of death with distinct symptoms with statistics can provide crucial decision-making inputs that some degree of accuracy (WHO 2007). For some areas of enable more efficient allocation of scarce financial the world verbal autopsies provide the only information resources towards the most pressing health needs (Murray about mortality currently available. Provided they can and Frenk 2008). Mortality statistics are a widely-used match or improve upon the accuracy of physician-coded resource for setting spending priorities, but out of 192 VA and expert algorithms, data-driven methods should be countries worldwide, only 23 have high-quality death used because they require less time from doctors or registration data, and 75 have no cause-specific mortality medical experts, and may provide valid reproducible fraction information at all (King and Lu 2008).

Evaluating new educational programs and tools, especially those targeted at difficult-to-assess learning goals can be quite challenging due to the small number of participants typically engaged with pilot programs. The focus of the evaluation, then, should be on collecting rich data from each participant about their experience in the workshop and their progress towards meeting the workshop’s learning goals. We present a novel evaluation technique, the debugging task, that seeks to assess at post-workshop a participant’s independent ability to use the tools, skills, and materials of the workshop. The technique is presented in the context of Robot Diaries, a program to develop a robotics design activity centered on crafts materials and expressiveness, and targeted to middle school girls. The paper discusses the rationale for the debugging task, its implementation, and the results and analyses of girls completing the task.

This paper presents an approach for mining agricultural problems that have been accumulated in a textual database over a period of 5 years. The problems, which are accompanied by their solutions, offer a wealth of knowledge that can be used by decision makers, researchers, and farmers alike. However, this wealth of knowledge can not be unlocked without a) representing these problems in a structured format, and b) applying algorithms that can summarize and analyze this information. Towards the achievement of the first goal, a multi-faceted object extraction methodology is presented, and for the achievement of the second, association rules are employed. As a proof of concept, the tool was applied of a set of weed problems. The presented methodology can be modified to work with any help and support textual database where both problems and their solutions are present.

In this paper, we describe our initial experiences using a mobile robot as a teaching aid in a stage movement class, taught in the Performing Arts Department of Washington University in St. Louis. The robot participated in a number of exercises, intended to teach the fundamentals of movement, and interacted closely with human acting students. We describe these exercises, what they are designed to teach the students, and discuss how using a robot as a teaching aid can enhance the students' experience. We describe two classes in which a robot participated, one under tele-operation and one fully autonomously, and discuss both the students' reaction to the robots, and our subjective evaluations of the systems success.

This paper presents a simulator that is being developed to study the performance of certain types of vehicle navigation. The performance metric looks at a likelihood of accomplishing a task and the cost of the strategy – measuring both robustness and efficiency. We present results involving only autonomous control strategies, yet the simulator will be used to compare human performance in completing the same task.

In visual metaphor processing, one object, the target, is compared to and understood in terms of another object, the source. Several studies suggest that perceptual similarity between two objects enhances a conceptual link between the two. However, little is known about how perceptual features contribute to the establishment of this link. In the present experiment we investigated the processing of the four possible combinations of conceptually and perceptually similar picture pairs using a same-different task. In order to determine whether particular processes are bound to a particular time range, we manipulated the delay between the two successively presented pictures. We expected perceptual processing effects at a short delay and conceptual processing effects at a longer delay. We did not find evidence for this expectation. However, the results did show that (i) it took participants longer to give a ‘different’ response if two objects shared perceptual features than when they did not; (ii) this presence of perceptual similarity also resulted in more response errors; and (iii) if objects shared only perceptual features, participants in the long delay condition produced more erroneous responses than the participants in the short delay condition did. These results are discussed in light of metaphor processing models.