Horizontal pressures in cylindrical metal silos and comparison with different international standards

The focus of this research was to evaluate the horizontal pressures on a cylindrical metal silo of corrugated walls and flat bottom with 1.82m diameter and 5.4m high, and to compare the values with those obtained theoretically by the ISO 11697, EP 433 and AS 3774 standards. The silo was symmetrically filled and constant speed with wheat cv. soft red for two different height/diameter ratios (H/D) and was unloaded through three orifices with a diameter of 71.6mm, one concentric and two eccentrics. Horizontal pressures were measured on the walls of the silo at three positions using hydraulic type pressure cells. The results showed that shortly after the start of the unloading, there was a mass flow above the quota of H/D = 1.2, whereas below this quota funnel flow occurred. It can be said that the EP 433 standard was more appropriate to predict horizontal pressures in silos in H/D ratio = 1.0, with eccentric unloading. For the H/D ratio = 1.5, AS 3774 standard was the one that produced values closer to the experimental

Modelling the “transactive memory system” in multimodal multiparty interactions

Transactive memory system (TMS) is a team emergent state representing the knowledge of each member about “who knows what” in a team performing a joint task. We present a study to show how the three TMS dimensions Credibility, Specialisation, Coordination, can be modelled as a linear combination of the nonverbal multimodal features displayed by the team performing the joint task. Results indicate that, to some extent, the three dimensions of TMS can be expressed as a linear combination of nonverbal multimodal features. Moreover, the higher the number of modalities (audio, movement, spatial), the better the modelling. Results could be used in future work to design human-centered computing applications able to automatically estimate TMS from teams’ behavioural patterns, to provide feedback and help teams’ interactions

The WoNoWa Dataset: Investigating the Transactive Memory System in Small Group Interactions

We present WoNoWa, a novel multi-modal dataset of small group interactions in collaborative tasks. The dataset is explicitly designed to elicit and to study over time a Transactive Memory System (TMS), a group's emergent state characterizing the group's meta-knowledge about "who knows what". A rich set of automatic features and manual annotations, extracted from the collected audio-visual data, is available on request for research purposes. Features include individual descriptors (e.g., position, Quantity of Motion, speech activity) and group descriptors (e.g., F-formations). Additionally, participants' self-assessments are available. Preliminary results from exploratory analyses show that the WoNoWa design allowed groups to develop a TMS that increased across the tasks. These results encourage the use of the WoNoWa dataset for a better understanding of the relationship between behavioural patterns and TMS, that in turn could help to improve group performance

How ECA vs Human Leaders Affect the Perception of Transactive Memory System (TMS) in a Team

Transactive Memory System (TMS) is a mental representation of the distribution of knowledge between the members of a team. Can an Embodied Conversational Agent perform as well as a Human when intervening as a leader to support the development of the team's TMS? And, if yes, are there differences in the way the team perceives their respective interventions? In this paper, a perceptive online study is conducted on how Human leader interventions affect the perception of a team's TMS. The results are compared to the ones from a previous study evaluating an Embodied Conversational agent leader rather than a human one. Both the agent and the human adopt nonverbal behaviors characterizing 2 leadership styles: Transformational (TFL) and Transactional (TAL). TFL is expected to stimulate team members curiosity and creativity in problem-solving; instead, TAL emphasizes the role of the leader in supervising the team, providing it with feedback when needed. The results show that the intervention from both the agent and the human are perceived to potentially improve the perceived TMS of a team. Another interesting insight is that the TFL style works better when performed by the Human, where both the TAL and TFL style perform well when realized by the agent

Vers des Agents Conversationnels Animés Socio-Affectifs

Dans cet article, nous proposons une architecture d'un Agent Conversationnel Animé (ACA) socio-affectif. Les différents modèles computationnels sous-jacents à cette architecture, permettant de donner la capacité à un ACA d'exprimer des émotions et des attitudes sociales durant son interaction avec l'utilisateur, sont présentés

Interpersonal Attitude of a Speaking Agent in Simulated Group Conversations

International audienceEmbodied Conversational Agents have been widely used to simulate dyadic interactions with users. We want to explore the context of expression of interpersonal attitudes in simulated group conversations. We are presenting a model that allows agents to exhibit a variety of non-verbal behaviors (e.g gestures, facial expressions, proxemics) depending on the interpersonal attitudes that they want to express within a group while talking. The model combines corpus-based and theoretical-based approaches and we present a preliminary implementation of this model