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This paper argues that hybrid human–agent systems can support powerful solutions to relevant problems such as Environmental Crisis management. However, it shows that such solutions require comprehensive approaches covering different aspects of data processing, model construction and the usage. In particular, the solutions (i) must be able to cope with complex correlations (as different data sources are used) and processing of large amounts of data, (ii) must be robust against modeling imperfections and (iii) human–machine interaction (HMI) approaches must facilitate human use of crisis management tools and reduce the likelihood of miscommunication.In this paper the relevant problem is an environmental protection application involving the detection and tracking of gases in case of chemical spills in an urban area. We show that a combination of Bayesian Networks, agent paradigm and systematic approaches to implementing HMI, support effective and robust solutions. To better integrate human information and demonstrate the usefulness of user generated crisis response information we developed a social media harvesting interface based on data from Twitter tweets and a visual interface to facilitate human smell classification.

Background: Medicinal plants remain an integral part of the lives of people in rural areas. The aim of this study was to document information about the medicinal plants used by Shangaan people in villages under Jongilanga tribal council, Bushbuckridge municipality, Mpumalanga Province, South Africa. Materials and Methods: An ethnobotanical survey of medicinal plants was conducted using a semi-structured questionnaire with 15 traditional healers as informants; one of them also served as a field guide during data collection. Results were analysed by using various quantitative indices of information consensus factor (ICF), use report (UR), frequency citation (FC) and relative frequency citation (RFC). Results and Methods: The study reported 86 medicinal plants used in villages for the treatment of various ailments, the majority (25 species) of which were used for urino-genital disorders. The Fabaceae family was the most represented family (17 species) of all the medicinal plants recorded in this study. The roots were the most frequently used plant part, accounting for 56% of the plants reported, and decoctions were often used in the preparation of herbal remedies. Respiratory diseases had the highest ICF value recorded among the 8 categories of ailments. The highest use report was reported for Combretum collinum (4), while the FC and RFC values (15) were highest in 12 plant species. The study revealed that medicinal plants are still widely used in rural areas and this documentation can serve as an ethno pharmacological basis for selecting plants with potential pharmaceutical properties.

We describe Castalia, a proposed mission to rendezvous with a Main Belt Comet (MBC), 133P/Elst-Pizarro. MBCs are a recently discovered population of apparently icy bodies within the main asteroid belt between Mars and Jupiter, which may represent the remnants of the population which supplied the early Earth with water. Castalia will perform the first exploration of this population by characterising 133P in detail, solving the puzzle of the MBC’s activity, and making the first in situ measurements of water in the asteroid belt. In many ways a successor to ESA’s highly successful Rosetta mission, Castalia will allow direct comparison between very different classes of comet, including measuring critical isotope ratios, plasma and dust properties. It will also feature the first radar system to visit a minor body, mapping the ice in the interior. Castalia was proposed, in slightly different versions, to the ESA M4 and M5 calls within the Cosmic Vision programme. We describe the science motivation for the mission, the measurements required to achieve the scientific goals, and the proposed instrument payload and spacecraft to achieve these.

This paper reports the application of results from human- social agent interaction experiments to inform the design of a social robot to monitor levels of pollutive gasses in the air. Next to licensed environmental agents and immobile chemical sensors, mobile technologies such as robotic agents are needed to collect complaints and smell descriptions from humans in urban industrial areas. These robots will interact with members of the public and ensure responsiveness and accuracy of responses. For robots to be accepted as representative environmental monitoring agents and for people to comply to robot instructions in the case of a calamity, social skills will be important. In this paper we will describe the intelligent environment the environmental robot is part of and discuss preliminary work on the effects of robot empathic and touch behaviors on human responses to robots. These and future findings will inform the design of social monitoring robot behaviors in public settings.

The work described in the present paper, performed as a part of the P2 project, presents an enhanced method to evaluate satellite vulnerability to micrometeoroids and orbital debris (MMOD), using the ESABASE2/Debris tool (developed under ESA contract). Starting from the estimation of induced failures on spacecraft (S/C) components and from the computation of lethal impacts (with an energy leading to the loss of the satellite), and considering the equipment redundancies and interactions between components, the debris-induced S/C functional impairment is assessed. The developed methodology, illustrated through its application to a case study satellite, includes the capability to estimate the number of failures on internal components, overcoming the limitations of current tools which do not allow propagating the debris cloud inside the S/C. The ballistic limit of internal equipment behind a sandwich panel structure is evaluated through the implementation of the Schafer Ryan Lambert (SRL) Ballistic Limit Equation (BLE). The analysis conducted on the case study satellite shows the S/C vulnerability index to be in the range of about 4% over the complete mission, with a significant reduction with respect to the results typically obtained with the traditional analysis, which considers as a failure the structural penetration of the satellite structural panels. The methodology has then been applied to select design strategies (additional local shielding, relocation of components) to improve S/C protection with respect to MMOD. The results of the analyses conducted on the improved design show a reduction of the vulnerability index of about 18%.

Being interrupted by notifications and reminders is common while working. In this study we consider whether system politeness reduces (negative) effects of being interrupted by system requests. We carried out a 2 (polite vs. neutral system request) x 2 (high vs. low mental load) between-participants experiment. We measured annoyance, frustration and mental effort. Our results suggest that social strategies can mitigate some of the negative effects, but that this depends on the difficulty of the task. We discuss the implications of these results for the design of interruptive system messages and for further research into social computing.

We present an application that facilitates environmental monitoring by and for the general public. 'Canary in a Coal Mine' (CIACM) gathers and analyses pollution-related tweets in real-time from the micro-blogging platform Twitter and visualizes temporal and spatial characteristics of the data. CIACM allows citizens to keep track of the environmental quality of their region and empowers users to contribute to this public environmental monitoring system.

This report presents the experiments that were carried out to investigate ways in which an intelligent adaptive interface could support inhabitants in providing accurate smell descriptions. We investigated the effect of multi-modal odor cues on human smell identification performance to inform the development of an adaptive interface for a mobile application. This involved a data elicitation study (N=429) to collect people’s olfactory associations when exposed to nine sample odors. Based on these associations, we then developed a multimodal interface that offered textual, image or combined cues to augment subjects’ odor perception, and 190 new subjects used the interface to identify odors. We found that participants’ smell identification performance increased when the interface offered visual (image and/or text) cues for odor identification. Furthermore, participants experienced the combination of visual and textual cues as most useful and enjoyable. The results of this experiment show that human smell perception can be successfully enhanced with the help of an adaptive odor cue interface. We have used the results of this study to develop a first prototype of an intelligent interface that automatically generates cues to assist human smell identification. This prototype is based on causal models (Bayesian Networks). We extracted these observation models for a few relevant chemicals. Due to the lack of data, all types of chemicals could not be covered. Nevertheless, we have shown that construction of models supporting detection and localization using human reports is possible.

Emotion has been found to influence humans’ cognitive information processing and decision-making (Schwarz, 2000). A state of sadness, for example, is accompanied by substantive information processing, with greater attention to detail, whereas people in a happier state tend to process information more heuristically. Mobile applications or services presenting information to users, especially those used primarily in emotionally laden contexts, could adapt information presentation to users’ current emotional state to improve compliance. This paper reports the results of an 2x2 between-subject survey experiment (N=91) with affective state (happy vs. sad) and information presentation style (heuristic vs. substantive) as dimensions. The results confirm that participants in a sad affective state are more likely to comply with mobile agents’ advice when information is tailored to a substantive processing style. They base decisions on substantive information and provide longer descriptions. In contrast, people in a happy affective state prefer heuristic information. These findings reinforce the importance of affect-sensitive adaptation, especially for mobile agents in potentially emotionally laden contexts.

Author(s): Winterboer, Diane E. | Abstract: More than 300 migratory bird species in Oregon have the potential to nest in highway rights-of-way or on bridges. Because these species are protected under the Migratory Bird Treaty Act (MBTA) and there are no incidental take permits, Oregon Department of Transportation (ODOT) projects may be impeded by nesting birds. In 2006, ODOT contacted USDA Wildlife Services to assist with MBTA compliance. This paper describes the unique nature of the inter-governmental agreement and the success it has brought both agencies.

This paper describes an experiment comparing the effect of two different approaches to information presentation on item recall. The results show that using discourse cues facilitates recalling the presented information.

In this paper we present results of a Wizard-of-Oz (WoZ) experiment comparing two approaches to information presentation in spoken dialogue systems. We show that the user-model based summarize- and-refine (UMSR) approach leads to increased task efficiency in comparison with the summarize-and-refine (SR) approach. Moreover, user ratings on four evaluation criteria demonstrated a clear preference for recommendations based on the UMSR approach to information presentation.

A 2x2 enhanced Wizard-of-Oz experiment (N = 32) was conducted to compare two different approaches to presenting information to drivers in easy and difficult driving conditions. Data of driving safety, evaluation of the spoken dialogue system, and perception of self were analyzed. Results show that the user-modeled summarizeand- refine (UMSR) approach led to more efficient information retrieval than did the summarize-and-refine (SR) approach. However, depending on driving condition, higher efficiency did not always translate into pleasant subjective experience. Implications for usability testing and interface design were presented, followed by discussions of future research directions.

This paper presents results of a Wizard-of-Oz (WoZ) study examining the effect of two different information presentation methods on a secondary task, namely driving. The results demonstrate that the user-model based summarize and refine(UMSR) approach enables more efficient information retrieval in comparison to the data-driven summarize and refine (SR) approach, and does not negatively affect driving performance.