scholarly journals GroupUs: Smartphone Proximity Data and Human Interaction Type Mining

2011 ◽  
Author(s):  
Trinh Minh Tri Do ◽  
Daniel Gatica-Perez
Keyword(s):  
Human Interaction ◽  
Interaction Type ◽  
Proximity Data

scholarly journals The Built Environment Is a Microbial Wasteland

mSystems ◽  
2016 ◽  
Vol 1 (2) ◽  
Author(s):  
Sean M. Gibbons
Keyword(s):  
Built Environment ◽  
Microbial Diversity ◽  
Microbial Communities ◽  
Human Interaction ◽  
Outdoor Environment ◽  
Sampling Location ◽  
Relative Importance ◽  
Surface Material ◽  
Interaction Type ◽  
Surface Location

ABSTRACT Humanity’s transition from the outdoor environment to the built environment (BE) has reduced our exposure to microbial diversity. The relative importance of factors that contribute to the composition of human-dominated BE microbial communities remains largely unknown. Humanity’s transition from the outdoor environment to the built environment (BE) has reduced our exposure to microbial diversity. The relative importance of factors that contribute to the composition of human-dominated BE microbial communities remains largely unknown. In their article in this issue, Chase and colleagues (J. Chase, J. Fouquier, M. Zare, D. L. Sonderegger, R. Knight, S. T. Kelley, J. Siegel, and J. G. Caporaso, mSystems 1(2):e00022-16, 2016, http://dx.doi.org/10.1128/mSystems.00022-16 ) present an office building study in which they controlled for environmental factors, geography, surface material, sampling location, and human interaction type. They found that surface location and geography were the strongest factors contributing to microbial community structure, while surface material had little effect. Even in the absence of direct human interaction, BE surfaces were composed of 25 to 30% human skin-associated taxa. The authors demonstrate how technical variation across sequencing runs is a major issue, especially in BE work, where the biomass is often low and the potential for PCR contaminants is high. Overall, the authors conclude that BE surfaces are desert-like environments where microbes passively accumulate.

scholarly journals Human-machine-human interaction in motor control and rehabilitation: a review

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Emek Barış Küçüktabak ◽  
Sangjoon J. Kim ◽  
Yue Wen ◽  
Kevin Lynch ◽  
Jose L. Pons
Keyword(s):  
Motor Control ◽  
Motor Learning ◽  
Task Performance ◽  
Human Interaction ◽  
Future Research ◽  
Physical Interaction ◽  
Interaction Type ◽  
Partner Characteristics ◽  
The Impact ◽  
Individual Motor

Abstract Background Human-human (HH) interaction mediated by machines (e.g., robots or passive sensorized devices), which we call human-machine-human (HMH) interaction, has been studied with increasing interest in the last decade. The use of machines allows the implementation of different forms of audiovisual and/or physical interaction in dyadic tasks. HMH interaction between two partners can improve the dyad’s ability to accomplish a joint motor task (task performance) beyond either partner’s ability to perform the task solo. It can also be used to more efficiently train an individual to improve their solo task performance (individual motor learning). We review recent research on the impact of HMH interaction on task performance and individual motor learning in the context of motor control and rehabilitation, and we propose future research directions in this area. Methods A systematic search was performed on the Scopus, IEEE Xplore, and PubMed databases. The search query was designed to find studies that involve HMH interaction in motor control and rehabilitation settings. Studies that do not investigate the effect of changing the interaction conditions were filtered out. Thirty-one studies met our inclusion criteria and were used in the qualitative synthesis. Results Studies are analyzed based on their results related to the effects of interaction type (e.g., audiovisual communication and/or physical interaction), interaction mode (collaborative, cooperative, co-active, and competitive), and partner characteristics. Visuo-physical interaction generally results in better dyadic task performance than visual interaction alone. In cases where the physical interaction between humans is described by a spring, there are conflicting results as to the effect of the stiffness of the spring. In terms of partner characteristics, having a more skilled partner improves dyadic task performance more than having a less skilled partner. However, conflicting results were observed in terms of individual motor learning. Conclusions Although it is difficult to draw clear conclusions as to which interaction type, mode, or partner characteristic may lead to optimal task performance or individual motor learning, these results show the possibility for improved outcomes through HMH interaction. Future work that focuses on selecting the optimal personalized interaction conditions and exploring their impact on rehabilitation settings may facilitate the transition of HMH training protocols to clinical implementations.

scholarly journals CLASSY: A Conversational Aware Suggestion System

Proceedings ◽  
2019 ◽  
Vol 31 (1) ◽  
pp. 40 ◽  
Author(s):  
Diogo Ferreira ◽  
Mário Antunes ◽  
Diogo Gomes ◽  
Rui L. Aguiar
Keyword(s):  
Retrieval System ◽  
Information Retrieval System ◽  
Human Interaction ◽  
Proximity Data ◽  
Pervasive Systems ◽  
Surrounding Environment ◽  
Pervasive System ◽  
The Relationship ◽  
Interesting Development ◽  
New Scoring

Over the last few years, pervasive systems have seen some interesting development. Nevertheless, human–human interaction can also take advantage of those systems by using their ability to perceive the surrounding environment. In this work, we have developed a pervasive system – named CLASSY – that is aware of the conversational context and suggests documents potentially useful to the users based on an Information Retrieval system, and proposed a new scoring approach that uses semantics and distance based on proximity data in order to classify the relationship between tokens.

Human Interaction: Understanding Is Not Enough

1974 ◽  
Vol 19 (7) ◽  
pp. 539-540
Author(s):  
NEWTON MARGULIES
Keyword(s):  
Human Interaction

A Comprehensive Model for Medical Information Processing

1983 ◽  
Vol 22 (03) ◽  
pp. 124-130 ◽  
Author(s):  
J. H. Bemmel
Keyword(s):  
Intensive Care ◽  
Information Processing ◽  
Medical Information ◽  
Computer Applications ◽  
Human Interaction ◽  
Comprehensive Model ◽  
Computers In Medicine ◽  
Medical Information Systems ◽  
Research And Education ◽  
The Many

At first sight, the many applications of computers in medicine—from payroll and registration systems to computerized tomography, intensive care and diagnostics—do make a rather chaotic impression. The purpose of this article is to propose a scheme or working model for putting medical information systems in order. The model comprises six »levels of complexity«, running parallel to dependence on human interaction. Several examples are treated to illustrate the scheme. The reason why certain computer applications are more frequently used than others is analyzed. It has to be strongly considered that the differences in complexity and dependence on human involvement are not accidental but fundamental. This has consequences for research and education which are also discussed.

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