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The monitoring of small houses and rooms has become possible due to the advances in IoT sensors, actuators and low power communication protocols in the last few years. As buildings are one of the biggest energy consuming entities, monitoring them has great interest for trying to avoid non-necessary energy waste. Moreover, human behaviour has been reported as being the main discrepancy source between energy usage simulations and real usage, so the ability to monitor and predict actions as opening windows, using rooms, etc. is gaining attention to develop stronger models which may lead to reduce the overall energy consumption of buildings, considering buildings thermal inertia and additional capabilities. In this paper, a case study is described in which four meeting rooms have been monitored to obtain information about the usage of the rooms and later use it to predict their future usage. The results show the possibility to deploy a simple and non-intrusive sensing system whose output could be used to develop advanced control strategies. This work was partially supported by the Department of Education, Universities and Research of the Basque Government (ADIAN research group, grant IT980-16) and by the Ministry of Economy and Competitiveness of the Spanish Government and the European Regional Development fund- ERDF (PhysComp project, TIN2017-85409-P).

Integrating culture into the behavioural models of virtual characters requires knowledge from very different disciplines such as cross-cultural psychology and computer science. If culture-related behavioural differences are simulated with a virtual character system, users might not necessarily understand the intent of the designer. This is, in part, due to the influence of culture on not only users, but also designers. To gain a greater understanding of the instantiation of culture in the behaviour of virtual characters, and on this potential mismatch between designer and user, we have conducted two experiments. In these experiments, we tried to simulate one dimension of culture (Masculinity vs. Femininity) in the behaviour of virtual characters. We created four scenarios in the first experiment and six in the second. In each of these scenarios, the same two characters interact with each other. The verbal and non-verbal behaviour of these characters differs depending on their cultural scripts. In two user perception studies, we investigated how these differences are judged by human participants with different cultural backgrounds. Besides expected differences between participants from Masculine and Feminine countries, we found significant differences in perception between participants from Individualistic and Collectivistic countries. We also found that the user's interpretation of the character's motivation had a significant influence on the perception of the scenarios. Based on our findings, we give recommendations for researchers that aim to design culture-specific behaviours for virtual characters.

International audience; The present investigation aims at evaluating and understanding the thermo-mechanical behaviour of a titanium alloy under hot forming conditions. In this work, several considerations are addressed. First, Scanning Electron Microscopy observations are performed to assess the evolutions of (α − β) phases, grain size, defects regarding the thermo-mechanical loadings from different static and dynamic tests (various temperatures and strain rates). Hence, the relationships between mechanical properties and micro-structure evolutions in such conditions allow a first assessment of the deformation mechanisms in link with the macroscopic stress-strain curves. Afterwards, a behaviour model formulation associated to an identification procedure of the parameters of the constitutive equations is proposed. Finally, several tests performed under hot forming conditions and conducted on an industrial press are compared to Finite Element calculations. Results are compared and provide some interesting improvement ways in order to investigate the influence of the process parameters on the final shape of the part.

The development of IoT devices has allowed to install large amounts of sensors in different environments. Consequently, monitoring small houses and entire buildings has become possible. In addition, buildings are one of the biggest energy consumers, so the monitoring of the energy waste, and its sources, is gaining attention. Human behaviour has been reported as being the main discrepancy source between energy usage simulations and real usage, thus being able to easily monitor such behaviour will bring greater insight in the building usage. In this paper, an IoT sensor network is proposed to model occupancy profiles at room level. Such measurement of users’ behaviour along with additional information such as temperature or humidity can be used to develop strategies to save energy, especially regarding heating, ventilating and airconditioning (HVAC) systems. The proposed equipment has been gathering data for some months in a workplace containing several meeting rooms. Four of those rooms were monitored and later analysed to test the validity of the proposed approach. The results show that it is possible to obtain occupancy profiles by using simple IoT equipment. Unai Saralegui is grateful to the Tecnalia Research & Innovation Foundation for funding through a PhD fellowship. Olatz Arbelaitz and Javier Muguerza’s research was partially supported by the Department of Education, Universities and Research of the Basque Government under Grant IT980- 16 and by the Ministry of Economy and Competitiveness of the Spanish Government and the European Regional Development fund- ERFD (PhysComp project, TIN2017- 85409-P).

Autonomous robotic systems operating in the vicinity of other agents, such as humans, manually driven vehicles and other robots, can model the behaviour and estimate intentions of the other agents to enhance efficiency of their operation, while preserving safety. We propose a data-driven approach to model the behaviour of other agents, which is based on a set of trajectories navigated by other agents. Then, to evaluate the proposed behaviour modelling approach, we propose and compare two methods for agent intention estimation based on: (i) particle filtering, and (ii) decision trees. The proposed methods were validated using three datasets that consist of real-world bicycle and car trajectories in two different scenarios, at a roundabout and at a t-junction with a pedestrian crossing. The results validate the utility of the data-driven behaviour model, and show that decision-tree based intention estimation works better on a binary-class problem, whereas the particle-filter based technique performs better on a multi-class problem, such as the roundabout, where the method yielded an average gain of 14.88 m for correct intention estimation locations compared to the decision-tree based method.

The complexity of interactions governing the coordination of loosely-coupled services, which forms the core of current software, brought behavioural issues up to the front of architectural concerns. This paper takes such a challenge seriously by lifting typical behaviour modelling techniques to the specification of both types and instances of architectural patterns in which the later ones are connected by ports that behave according to a water flow metaphor. A specific language is introduced for this purpose as well as a translator to mCRL2 so that the simulation and analysis techniques available in the corresponding toolset can be used to reason about (the behavioural layer of) software architectures. The approach is illustrated in a few examples, (undefined)

Issu de : 7th International tooling conference on tooling materials and their applications from research to market, Torino, ITALY, 2-5 May 2006; International audience; The cyclic behaviour of X38CrMoV5 (AISI H11) tool steel with a nominal hardness of 47HRC has been predicted. Basically, thermo-elastoplastic and thermo-elastoviscoplastic constitutive laws are investigated. First, various uniaxial isothermal conditions (LCF) with different strain rate, strain amplitude and temperature level are investigated. Then the constitutive laws are examined under various TMF loading conditions. The simulated results by both the approaches are compared with experimental results in terms of stress?strain behaviour and cyclic softening. Some applications of the model for simulation of thermal fatigue sample are shown. Taking into consideration the results of this work, the goal is to further characterise the limitations of these constitutive laws under complex and severe loading conditions, i.e., under variable temperature, variable strain amplitude and thermal fatigue structural specimen.