ETHNIC DISPLACEMENT IN THE INTERSTITIAL COMMUNITY: THE EAST HARLEM (NEW YORK CITY) EXPERIENCE

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Emotional virtual agents: How do young people decode synthetic facial expressions?

Given the need of remote learning and the growing presence of virtual agents within online learning environments, the present research aims at investigating young people’ ability to decode emotional expressions conveyed by virtual agents. The study, involves 50 healthy participants aged between 22 and 35 years (mean age=27.86; SD= ±2.75; 30 females) which were required to label pictures and video clips depicting female and male virtual agents of different ages (young, middle-aged and old) displaying static and dynamic expressions of disgust, anger, sadness, fear, happiness, surprise and neutrality. Depending on the emotional category, significant effects were observed for the agents’ age, gender, and type of administered (static vs dynamic) stimuli on the young people’ decoding accuracy of the virtual agents’ emotional faces. Anger was significantly more accurately decoded in male rather than female faces while the opposite result was observed for happy, fearful, surprised, and disgusted faces. Middle aged faces were generally more accurately decoded than young and old emotional faces except for sadness and disgust. Significantly greater accuracy was observed for dynamic vs static faces of disgust, sadness, and fear, in contrast to static vs dynamic neutral and surprised faces

A Study on the Parallelization of Terrain-Covering Ant Robots Simulations

Agent-based simulation is used as a tool for supporting (time-critical) decision making in differentiated contexts. Hence, techniques for speeding up the execution of agent-based models, such as Parallel Discrete Event Simulation (PDES), are of great relevance/benefit. On the other hand, parallelism entails that the final output provided by the simulator should closely match the one provided by a traditional sequential run. This is not obvious given that, for performance and efficiency reasons, parallel simulation engines do not allow the evaluation of global predicates on the simulation model evolution with arbitrary time-granularity along the simulation time-Axis. In this article we present a study on the effects of parallelization of agent-based simulations, focusing on complementary aspects such as performance and reliability of the provided simulation output. We target Terrain Covering Ant Robots (TCAR) simulations, which are useful in rescue scenarios to determine how many agents (i.e., robots) should be used to completely explore a certain terrain for possible victims within a given time. © 2014 Springer-Verlag Berlin Heidelberg

Behavioral sentiment analysis of depressive states

The need to release accurate and incontrovertible diagnoses of depression has fueled the search for new methodologies to obtain more reliable measurements than the commonly adopted questionnaires. In such a context, research has sought to identify non-biased measures derived from analyses of behavioral data such as voice and language. For this purpose, sentiment analysis techniques were developed, initially based on linguistic characteristics extracted from texts and gradually becoming more and more sophisticated by adding tools for the analyses of voice and visual data (such as facial expressions and movements). This work summarizes the behavioral features accounted for detecting depressive states and sentiment analysis tools developed to extract them from text, audio, and video recordings

Humanoid and android robots in the imaginary of adolescents, young adults and seniors

This paper investigates effects of participants’ gender and age (adolescents, young adults, and seniors), robots’ gender (male and female robots) and appearance (humanoid vs android) on robots’ acceptance dimensions. The study involved 6 differently aged groups of participants (two adolescents, two young adults and two seniors’ groups, for a total of 240 participants) requested to express their willingness to interact and their perception of robots’ usefulness, pleasantness, appeal, and engagement for two different sets of females (Pepper, Erica, and Sophia) and male (Romeo, Albert, and Yuri) humanoid and android robots. Participants were also requested to express their preferred and attributed age ranges and occupations they entrusted to robots among healthcare, housework, protection and security and front office. Results show that neither the age nor participants and robots’ gender, nor robots’ human likeness univocally affected robots’ acceptance by these differently aged users. Robots’ acceptance appeared to be a nonlinear combination of all these factors

Ethical issues in assistive ambient living technologies for ageing well

Assistive Ambient Living (AAL) in ageing refers to any device used to support ageing related psychological and physical changes aimed at improving seniors’ quality of life and reducing caregivers’ burdens. The diffusion of these devices opens the ethical issues related to their use in the human personal space. This is particularly relevant when AAL technologies are devoted to the ageing population that exhibits special bio-psycho-social aspects and needs. In spite of this, relatively little research has focused on ethical issues that emerge from AAL technologies. The present article addresses ethical issues emerging when AAL technologies are implemented for assisting the elderly population and is aimed at raising awareness of these aspects among healthcare providers. The overall conclusion encourages a person-oriented approach when designing healthcare facilities. This process must be fulfilled in compliance with the general principles of ethics and individual nature of the person devoted to. This perspective will develop new research paradigms, paving the way for fulfilling essential ethical principles in the development of future generations of personalized AAL devices to support ageing people living independently at their home

Programmability and Performance of Parallel ECS-based Simulation of Multi-Agent Exploration Models

While the traditional objective of parallel/distributed simulation techniques has been mainly in improving performance and making very large models tractable, more recent research trends targeted complementary aspects, such as the “ease of programming”. Along this line, a recent proposal called Event and Cross State (ECS) synchronization, stands as a solution allowing to break the traditional programming rules proper of Parallel Discrete Event Simulation (PDES) systems, where the application code processing a specific event is only allowed to access the state (namely the memory image) of the target simulation object. In fact with ECS, the programmer is allowed to write ANSI-C event-handlers capable of accessing (in either read or write mode) the state of whichever simulation object included in the simulation model. Correct concurrent execution of events, e.g., on top of multi-core machines, is guaranteed by ECS with no intervention by the programmer, who is in practice exposed to a sequential-style programming model where events are processed one at a time, and have the ability to access the current memory image of the whole simulation model, namely the collection of the states of any involved object. This can strongly simplify the development of specific models, e.g., by avoiding the need for passing state information across concurrent objects in the form of events. In this article we investigate on both programmability and performance aspects related to developing/supporting a multi-agent exploration model on top of the ROOT-Sim PDES platform, which supports ECS

Discriminative power of EEG-based biomarkers in major depressive disorder: A systematic review

Currently, the diagnosis of major depressive disorder (MDD) and its subtypes is mainly based on subjective assessments and self-reported measures. However, objective criteria as Electroencephalography (EEG) features would be helpful in detecting depressive states at early stages to prevent the worsening of the symptoms. Scientific community has widely investigated the effectiveness of EEG-based measures to discriminate between depressed and healthy subjects, with the aim to better understand the mechanisms behind the disorder and find biomarkers useful for diagnosis. This work offers a comprehensive review of the extant literature concerning the EEG-based biomarkers for MDD and its subtypes, and identify possible future directions for this line of research. Scopus, PubMed and Web of Science databases were researched following PRISMA’s guidelines. The initial papers’ screening was based on titles and abstracts; then full texts of the identified articles were examined, and a synthesis of findings was developed using tables and thematic analysis. After screening 1871 articles, 76 studies were identified as relevant and included in the systematic review. Reviewed markers include EEG frequency bands power, EEG asymmetry, ERP components, non-linear and functional connectivity measures. Results were discussed in relations to the different EEG measures assessed in the studies. Findings confirmed the effectiveness of those measures in discriminating between healthy and depressed subjects. However, the review highlights that the causal link between EEG measures and depressive subtypes needs to be further investigated and points out that some methodological issues need to be solved to enhance future research in this field

Frontal left alpha activity as an indicator of willingness to interact with virtual agents: A pilot study

Over the last decade, much effort has been made to develop virtual agents acting as assistants of elderly people in their daily activities. With the emergence of such technologies, several questionnaires have been developed to investigate the factors increasing user's acceptance of virtual agents. While questionnaires provide detailed information about users' preferences, they may not be sufficient for investigating user's internal affective states and impressions during the interaction with virtual agents. Therefore, improving assessment techniques for elders' acceptance of virtual agents is necessary for understanding the impressions they arouse and determining their design accordingly. This paper is a report of a pilot study that benefits from the predictive ability of left frontal alpha activity in the brain on positive affect and approach related motivation, and investigates relationships between user's willingness to interact with virtual agents and left frontal alpha activity in order to gain insights on user's affective and motivational states during the interaction with an agent

How Human Likeness, Gender and Ethnicity affect Elders'Acceptance of Assistive Robots

The present study investigates the extent to which robots' 1) degree of human likeness, 2) gender and 3) ethnicity affect elders' attitude towards using robots as healthcare assistants. To this aim 2 groups of 45 seniors, aged 65 + years, were asked to watch video clips showing three speaking female and male robots, respectively. Each set of stimuli consisted in 2 androids, one with Caucasian and one with Asian aspect, and 1 humanoid robot. After each video clip elders were asked to assess, through the Robot Acceptance Questionnaire (RAQ) their willingness to interact with them, as well as robots' Pragmatic, Hedonic and Attractive qualities. Through this investigation it was found that male seniors were more proactive than female ones in their attitude toward robots showing more willingness to interact with them and attributing more positive scores to robots' qualities. It was also observed that androids were clearly more preferred than humanoid robots no matter their gender. Finally, seniors' preferences were for female android robots with Asian traits and male android with Caucasian traits suggesting that both gender and ethnical features are intermingled in defining robot's appearance that generate seniors' acceptance