MUVTIME: a Multivariate time series visualizer for behavioral science

As behavioral science becomes progressively more data driven, the need is increasing for appropriate tools for visual exploration and analysis of large datasets, often formed by multivariate time series. This paper describes MUVTIME, a multimodal time series visualization tool, developed in Matlab that allows a user to load a time series collection (a multivariate time series dataset) and an associated video. The user can plot several time series on MUVTIME and use one of them to do brushing on the displayed data, i.e. select a time range dynamically and have it updated on the display. The tool also features a categorical visualization of two binary time series that works as a high-level descriptor of the coordination between two interacting partners. The paper reports the successful use of MUVTIME under the scope of project TURNTAKE, which was intended to contribute to the improvement of human-robot interaction systems by studying turn- taking dynamics (role interchange) in parent-child dyads during joint action.Marie Curie International Incoming Fellowship PIIF-GA-2011- 301155; Portuguese Foundation for Science and Technology (FCT) project PTDC/PSI- PCO/121494/2010; AFP was also partially funded by the FCT project (IF/00217/2013)This research was supported by: Marie Curie International Incoming Fellowship PIIF-GA-2011301155; Portuguese Foundation for Science and Technology (FCT) Strategic program FCT UID/EEA/00066/2013; FCT project PTDC/PSIPCO/121494/2010. AFP was also partially funded by the FCT project (IF/00217/2013). REFERENCE

Involving Users to Improve the Collaborative Logical Framework

In order to support collaboration in web-based learning, there is a need for an intelligent support that facilitates its management during the design, development, and analysis of the collaborative learning experience and supports both students and instructors. At aDeNu research group we have proposed the Collaborative Logical Framework (CLF) to create effective scenarios that support learning through interaction, exploration, discussion, and collaborative knowledge construction. This approach draws on artificial intelligence techniques to support and foster an effective involvement of students to collaborate. At the same time, the instructors’ workload is reduced as some of their tasks—especially those related to the monitoring of the students behavior—are automated. After introducing the CLF approach, in this paper, we present two formative evaluations with users carried out to improve the design of this collaborative tool and thus enrich the personalized support provided. In the first one, we analyze, following the layered evaluation approach, the results of an observational study with 56 participants. In the second one, we tested the infrastructure to gather emotional data when carrying out another observational study with 17 participants

2016 IMSAloquium, Student Investigation Showcase

Welcome to the twenty-eighth year of the Student Inquiry and Research Program (SIR)! This is a program that is as old as IMSA. The SIR program represents our unending dedication to enabling our students to learn what it is to be an innovator and to make contributions to what is known on Earth.https://digitalcommons.imsa.edu/archives_sir/1026/thumbnail.jp

A Celebration of West Point Authors

Today we celebrate the more than 200 works of scholarship produced at the Academy between July and December 2017. The theme of this event is the intersection of civilian and military technology, policy, and innovation.https://digitalcommons.usmalibrary.org/books/1013/thumbnail.jp

Linking communicative interaction to cognitive functioning: implications for older adults

As the percentage of older adults within the U.S. steadily increases, long-term care options are being impacted with growing numbers of seniors to provide for. The reality of these elevated numbers have sparked an interest in researchers to conduct studies on human development, plasticity in the brain, and training and intervention programs in search for ways to halt or lessen the cognitive and communicative decline, in older adults. As an alternative path to help older adults maintain quality of life, this study proposes to examine the link between communicative interaction and cognitive functioning to educate family members and healthcare providers on how communicative interactions and language influence cognition. Data (n = 3130) used in this study was retrieved from the University of Michigan’s Health and Retirement Study (HRS) 2014 for participants 65 years and older. Examination of the link between communicative interaction and cognition encompassed all factors of the learning process such as socio-emotional influences, environmental experiences, health and nutrition, and cognitive and physical development. Analysis of the study also included exploratory studies on social cognitive neuroscience and how brain training affects dementia. Findings in this study revealed that cognitive functioning declines with age, but rises with higher levels of education. Results also indicate that increased communicative interaction is significantly associated with improved cognitive functioning, when controlling for age, gender, and education. Considering other influential factors, determining the degree of association may require further investigation

Análise computacional de aspetos de comunicação não verbal em contextos de grupo

Human communication is a major field of study in psychology and social sciences. Topics such as emergent leadership and group dynamics are commonly studied cases when referring to group settings. Experiments regarding group settings are usually analyzed in conversational and collaborative tasks environments in order to study the communication process in small groups. Former studies’ methods involve human analysis and manual annotation of others’ behaviors in communication settings. Later studies try to replace time consuming and failure prone annotations by resorting to computational methods. Having a custom, newly-gathered audiovisual dataset, from an experiment conducted by the Department of Education and Psychology of the University of Aveiro, a multidisciplinary group from the same institution with members from psychology and engineering backgrounds, took the initiative to create computational methods in order to facilitate the analysis of the collected data. For that purpose, this work presents a multimodal computational framework using state-of-the-art methods in computer vision, capable of enriching image data with annotations of a broad range of nonverbal communication aspects, both at an individual and group levels, thus facilitating the study of nonverbal communication and group dynamics. This works contributes to the community by presenting methods to directly increase human knowledge about the human communication process, involving data transformation processes in order to transform raw feature data into humanly understandable meanings and a visualization tool capable of visualizing such methods applied to the input data.A comunicação humana é uma grande área de estudo na psicologia e ciências sociais. Temas como liderança emergente e dinâmicas de grupo são temas frequentemente estudados quando se estudam contextos de grupo. Dentro da área de estudos sobre contextos de grupo analisam-se situações de conversação e realização de tarefas colaborativas em grupos de pequena dimensão. Estudos primordiais envolviam análise e anotação humana para a anotação dos comportamentos revelados nas experiências realizadas, equanto que estudos mais recentes tendem a adotar métodos computacionais de forma a susbtituir os métodos anteriormente usados por serem dispendiosos em termos de tempo e propícios a erros. Tendo como caso de estudo um conjunto de dados audiovisuais de uma experiência realizada pelo Departamento de Educação e Psicologia da Universidade de Aveiro, um grupo de investigação multidisciplinar das áreas da psicologia e engenharia tomou a iniciativa de desenvolver métodos computacionais capazes de facilitar o processo de análise dos dados recolhidos. Como tal, este trabalho apresenta uma abordagem computacional multimodal, utilizando métodos "Estado da arte", capaz de enriquecer os dados visuais com anotações de uma larga extensão de aspetos de comunicação não-verbal, tanto a nível individual como de grupo, facilitando assim o estudo da comunicação em geral e das dinâmicas de grupo. Este trabalho contribui para a comunidade, fornecendo métodos para aumentar o conhecimento existente sobre o processo de comunicação humana, incluindo processos de transformação de dados, desde dados numéricos de baixa interpretação para informação interpretável e compreensível, assim como uma ferramenta de visualização capaz de apresentar tais métodos aplicados aos dados de entrada.Mestrado em Engenharia Informátic