This paper investigates adaptive thermal comfort during summer in medical residences that are located in the French city of Troyes and managed by the Association of Parents of Disabled Children (APEI). Thermal comfort in these buildings is evaluated using subjective measurements and objective physical parameters. The thermal sensations of respondents were determined by questionnaires, while thermal comfort was estimated using the predicted mean vote (PMV) model. Indoor environmental parameters (relative humidity, mean radiant temperature, air temperature, and air velocity) were measured using a thermal environment sensor during the summer period in July and August 2018. A good correlation was found between operative temperature, mean radiant temperature, and PMV. The neutral temperature was determined by linear regression analysis of the operative temperature and Fanger’s PMV model. The obtained neutral temperature is 23.7 °C. Based on the datasets and questionnaires, the adaptive coefficient α representing patients’ capacity to adapt to heat was found to be 1.261. A strong correlation was also observed between the sequential thermal index $\mathrm{n}\left(\mathrm{t}\right)$ and the adaptive temperature. Finally, a new empirical model of adaptive temperature was developed using the data collected from a longitudinal survey in four residential buildings of APEI in summer, and the obtained adaptive temperature is 25.0 °C with upper and lower limits of 24.7 °C and 25.4 °C.

Tasks such as distinguishing or identifying individual objects of interest require the production of dense local clouds at the scale of these individual objects of interest. Due to the physical and dynamic properties of an underwater environment, the usual dense matching algorithms must be rethought in order to be adaptive. These properties also imply that the scene must be observed at close range. Classic robotized acquisition systems are oversized for local studies in shallow water while the systematic acquisition of data is not guaranteed with divers. We address these two major issues through a multidisciplinary approach. To efficiently acquire on-demand stereoscopic pairs using simple logistics in small areas of shallow water, we devised an agile light-weight dedicated system which is easy to reproduce. To densely match two views in a reliable way, we devised a reconstruction algorithm that automatically accounts for the dynamics, variability and light absorption of the underwater environment. Field experiments in the Mediterranean Sea were used to assess the results.