Socially impaired robots: Human social disorders and robots’ socio-emotional intelligence

© Springer International Publishing Switzerland 2014. Social robots need intelligence in order to safely coexist and interact with humans. Robots without functional abilities in understanding others and unable to empathise might be a societal risk and they may lead to a society of socially impaired robots. In this work we provide a survey of three relevant human social disorders, namely autism, psychopathy and schizophrenia, as a means to gain a better understanding of social robots’ future capability requirements.We provide evidence supporting the idea that social robots will require a combination of emotional intelligence and social intelligence, namely socio-emotional intelligence. We argue that a robot with a simple socio-emotional process requires a simulation-driven model of intelligence. Finally, we provide some critical guidelines for designing future socio-emotional robots

PAH emissions from an African cookstove

Combustion of wood and other biomass is a significant contributor to poor air quality in many developing countries. Emissions of particulates and Polycyclic Aromatic Hydrocarbons (PAH) are a major health hazard, particularly in Africa where the use of domestic cookstoves has increased alongside population expansion. Because of economic factors firewood is commonly used in place of the more expensive charcoal; particularly in rural areas. This work conducts a study of PAH emissions from an African cookstove comparing the combustion of both charcoal and firewood. It is demonstrated that PAH and particulate emissions are much higher from the firewood compared to the charcoal. The difference in levels can be interpreted due to the importance of the pyrolysis reactions of the volatile components of wood in PAH formation, whereas these volatiles emissions are much smaller from charcoal. Analysis of the combustion phases (flaming, smouldering) is undertaken and a computer model has been developed to link the composition of the fuels to the emissions of the PAH and particulates. The modelled PAH levels are shown to follow a similar trend to the experimental results

Using Virtual Agents to Guide Attention in Multi-task Scenarios

Kulms P, Kopp S. Using Virtual Agents to Guide Attention in Multi-task Scenarios. In: Aylett R, Krenn B, Pelachaud C, Shimodaira H, eds. Intelligent Virtual Agents. Lecture Notes in Computer Science. Vol 8108. Berlin, Heidelberg: Springer Berlin Heidelberg; 2013: 295-302

Reference intervals for LC-MS/MS measurements of plasma free, urinary free and urinary acid-hydrolyzed deconjugated normetanephrine, metanephrine and methoxytyramine

Contains fulltext : 201350.pdf (publisher's version ) (Open Access

Detection of Head Pose and Gaze Direction for Human-Computer Interaction

Abstract. In this contribution we extend existing methods for head pose estimation and investigate the use of local image phase for gaze de-tection. Moreover we describe how a small database of face images with given ground truth for head pose and gaze direction was acquired. With this database we compare two different computational approaches for ex-tracting the head pose. We demonstrate that a simple implementation of the proposed methods without extensive training sessions or calibration is sufficient to accurately detect the head pose for human-computer in-teraction. Furthermore, we propose how eye gaze can be extracted based on the outcome of local filter responses and the detected head pose. In all, we present a framework where different approaches are combined to a single system for extracting information about the attentional state of a person

Reference intervals for plasma concentrations of adrenal steroids measured by LC-MS/MS: Impact of gender, age, oral contraceptives, body mass index and blood pressure status

Contains fulltext : 174653.pdf (Publisher’s version ) (Open Access)BACKGROUND: Mass spectrometric-based measurements of the steroid metabolome have been introduced to diagnose disorders featuring abnormal steroidogenesis. Defined reference intervals are important for interpreting such data. METHODS: Liquid chromatography-tandem mass spectrometry was used to establish reference intervals for 16 steroids (pregnenolone, progesterone, 11-deoxycorticosterone, corticosterone, aldosterone, 18-oxocortisol, 18-hydroxycortisol, 17-hydroxyprogesterone, 21-deoxycortisol, 11-deoxycortisol, cortisol, cortisone, dehydroepiandrosterone, dehydroepiandrosterone-sulfate, androstenedione, testosterone) measured in plasma from 525 volunteers with (n=227) and without (n=298) hypertension, including 68 women on oral contraceptives. RESULTS: Women showed variable plasma concentrations of several steroids associated with menstrual cycle phase, menopause and oral contraceptive use. Progesterone was higher in females than males, but most other steroids were higher in males than females and almost all declined with advancing age. Using models that corrected for age and gender, body mass index showed weak negative relationships with corticosterone, 21-deoxycortisol, cortisol, cortisone, testosterone, progesterone, 17-hydroxyprogesterone and 11-deoxycorticosterone, but a positive relationship with 18-hydroxycortisol. Hypertensives and normotensives showed negligible differences in plasma concentrations of steroids. CONCLUSION: Age and gender are the most important variables for plasma steroid reference intervals, which have been established here according to those variables for a panel of 16 steroids primarily useful for diagnosis and subtyping of patients with endocrine hypertension

Recognizing the Visual Focus of Attention for Human Robot Interaction

Sheikhi S, Odobez J-M. Recognizing the Visual Focus of Attention for Human Robot Interaction. In: Salah AA, Ruiz-del-Solar J, Meriçli Ç, Oudeyer P-Y, eds. Human Behavior Understanding. Lecture Notes in Computer Science. Vol 7559. Berlin, Heidelberg: Springer Berlin Heidelberg; 2012: 99-112.We address the recognition of people’s visual focus of attention (VFOA), the discrete version of gaze that indicates who is looking at whom or what. As a good indicator of addressee-hood (who speaks to whom, and in particular is a person speaking to the robot) and of people’s interest, VFOA is an important cue for supporting dialog modelling in Human-Robot interactions involving multiple persons. In absence of high definition images, we rely on people’s head pose to recognize the VFOA. Rather than assuming a fixed mapping between head pose directions and gaze target directions, we investigate models that perform a dynamic (temporal) mapping implicitly accounting for varying body/shoulder orientations of a person over time, as well as unsupervised adaptation. Evaluated on a public dataset and on data recorded with the humanoid robot Nao, the method exhibit better adaptivity and versatility producing equal or better performance than a state-of-the-art approach, while the proposed unsupervised adaptation does not improve results