Identifying Functions and Behaviours of Social Robots for In-Class Learning Activities: Teachers’ Perspective

International audienceWith advances in artificial intelligence, research is increasingly exploring the potential functions that social robots can play in education. As teachers are a critical stakeholder in the use and application of educational technologies, we conducted a study to understand teachers' perspectives on how a social robot could support a variety of learning activities in the classroom. Through interviews, robot puppeteering, and group brainstorming sessions with five elementary and middle school teachers, we take a sociotechnical perspective to conceptualize possible robot functions and behaviours, and the effects they may have on the current way learning activities are designed, planned, and executed. Using activity theory to analyze learning activities as an activity system illustrated a number of tensions that currently exist between the components of the system. Overall, the teachers responded positively to the idea of introducing a social robot as a technological tool for learning activities, envisioning differences in usage for teacher-robot and student-robot interactions. We discuss the fine-grained functions and behaviours envisioned by teachers, and how they address the current tensions-providing suggestions for improving the design of social robots for learning activities

What is a Paraconsistent Logic?

Paraconsistent logics are logical systems that reject the classical principle, usually dubbed Explosion, that a contradiction implies everything. However, the received view about paraconsistency focuses only the inferential version of Explosion, which is concerned with formulae, thereby overlooking other possible accounts. In this paper, we propose to focus, additionally, on a meta-inferential version of Explosion, i.e. which is concerned with inferences or sequents. In doing so, we will offer a new characterization of paraconsistency by means of which a logic is paraconsistent if it invalidates either the inferential or the meta-inferential notion of Explosion. We show the non-triviality of this criterion by discussing a number of logics. On the one hand, logics which validate and invalidate both versions of Explosion, such as classical logic and Asenjo–Priest’s 3-valued logic LP. On the other hand, logics which validate one version of Explosion but not the other, such as the substructural logics TS and ST, introduced by Malinowski and Cobreros, Egré, Ripley and van Rooij, which are obtained via Malinowski’s and Frankowski’s q- and p-matrices, respectively

CASE – Centre Asie du Sud-Est

Pierre-Yves Manguin, directeur d’études à l’EFEOÉric Bourdonneau, maître de conférences à l’EFEO Histoire et archéologie de l’ancienne Asie du Sud-Est Thématique 1 (Pierre-Yves Manguin) : Les premiers « âges du commerce » dans l’ancienne Asie du Sud-Est : échanges, réseaux, marchés Les systèmes politiques côtiers de l’Asie du Sud-Est, à compter des environs du Ve siècle av. notre ère, se sont développés au gré des fluctuations des échanges maritimes, à l’échelle de la région, entre les deux r..

CASE – Centre Asie du Sud-Est

Pierre-Yves Manguin, directeur d’études à l’EFEOÉric Bourdonneau, maître de conférences à l’EFEO Histoire et archéologie de l’ancienne Asie du Sud-Est Thématique 1 (Pierre-Yves Manguin) : Les premiers « âges du commerce » dans l’ancienne Asie du Sud-Est : échanges, réseaux, marchés Les systèmes politiques côtiers de l’Asie du Sud-Est, à compter des environs du Ve siècle av. notre ère, se sont développés au gré des fluctuations des échanges maritimes, à l’échelle de la région, entre les deux r..

Expression of Curiosity in Social Robots: Design, Perception, and Effects on Behaviour

International audienceCuriosity -the intrinsic desire for new information-can enhance learning, memory, and exploration. Therefore, understanding how to elicit curiosity can inform the design of educational technologies. In this work, we investigate how a social peer robot's verbal expression of curiosity is perceived, whether it can aect the emotional feeling and behavioural expression of curiosity in students, and how it impacts learning. In a between-subjects experiment, 30 participants played the game LinkIt!, a game we designed for teaching rock classication, with a robot verbally expressing: curiosity, curiosity plus rationale, or no curiosity. Results indicate that participants could recognize the robot's curiosity and that curious robots produced both emotional and behavioural curiosity contagion eects in participants

Bridging the gap between systems biology and medicine

Systems biology has matured considerably as a discipline over the last decade, yet some of the key challenges separating current research efforts in systems biology and clinically useful results are only now becoming apparent. As these gaps are better defined, the new discipline of systems medicine is emerging as a translational extension of systems biology. How is systems medicine defined? What are relevant ontologies for systems medicine? What are the key theoretic and methodologic challenges facing computational disease modeling? How are inaccurate and incomplete data, and uncertain biologic knowledge best synthesized in useful computational models? Does network analysis provide clinically useful insight? We discuss the outstanding difficulties in translating a rapidly growing body of data into knowledge usable at the bedside. Although core-specific challenges are best met by specialized groups, it appears fundamental that such efforts should be guided by a roadmap for systems medicine drafted by a coalition of scientists from the clinical, experimental, computational, and theoretic domains

Age and sex associate with outcome in older AML and high risk MDS patients treated with 10-day decitabine

Treatment choice according to the individual conditions remains challenging, particularly in older patients with acute myeloid leukemia (AML) and high risk myelodysplastic syndrome (MDS). The impact of performance status, comorbidities, and physical functioning on survival is not well defined for patients treated with hypomethylating agents. Here we describe the impact of performance status (14% ECOG performance status 2), comorbidity (40% HCT-comorbidity index ≥ 2), and physical functioning (41% short physical performance battery  76 years was significantly associated with reduced OS (HR 1.58; p = 0.043) and female sex was associated with superior OS (HR 0.62; p = 0.06). We further compared the genetic profiles of these subgroups. This revealed comparable mutational profiles in patients younger and older than 76 years, but, interestingly, revealed significantly more prevalent mutated ASXL1, STAG2, and U2AF1 in male compared to female patients. In this cohort of older patients treated with decitabine age and sex, but not comorbidities, physical functioning or cytogenetic risk were associated with overall survival

Bridging the Gap between Field Experiments and Machine Learning: The EC H2020 B-GOOD Project as a Case Study towards Automated Predictive Health Monitoring of Honey Bee Colonies.

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies' exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony's health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project's data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping

Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study

The VESSEL12 (VESsel SEgmentation in the Lung) challenge objectively compares the performance of different algorithms to identify vessels in thoracic computed tomography (CT) scans. Vessel segmentation is fundamental in computer aided processing of data generated by 3D imaging modalities. As manual vessel segmentation is prohibitively time consuming, any real world application requires some form of automation. Several approaches exist for automated vessel segmentation, but judging their relative merits is difficult due to a lack of standardized evaluation. We present an annotated reference dataset containing 20 CT scans and propose nine categories to perform a comprehensive evaluation of vessel segmentation algorithms from both academia and industry. Twenty algorithms participated in the VESSEL12 challenge, held at International Symposium on Biomedical Imaging (ISBI) 2012. All results have been published at the VESSEL12 website http://vessel12.grand-challenge.org. The challenge remains ongoing and open to new participants. Our three contributions are: (1) an annotated reference dataset available online for evaluation of new algorithms; (2) a quantitative scoring system for objective comparison of algorithms; and (3) performance analysis of the strengths and weaknesses of the various vessel segmentation methods in the presence of various lung diseases.Rudyanto, RD.; Kerkstra, S.; Van Rikxoort, EM.; Fetita, C.; Brillet, P.; Lefevre, C.; Xue, W.... (2014). Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study. Medical Image Analysis. 18(7):1217-1232. doi:10.1016/j.media.2014.07.003S1217123218