Open University of Catalonia

About: Open University of Catalonia is a education organization based out in Barcelona, Spain. It is known for research contribution in the topics: Collaborative learning & Educational technology. The organization has 1943 authors who have published 4646 publications receiving 64200 citations. The organization is also known as: Universitat Oberta de Catalunya & UOC.

I3Mote: An Open Development Platform for the Intelligent Industrial Internet.

Abstract: In this article we present the Intelligent Industrial Internet (I3) Mote, an open hardware platform targeting industrial connectivity and sensing deployments. The I3Mote features the most advanced low-power components to tackle sensing, on-board computing and wireless/wired connectivity for demanding industrial applications. The platform has been designed to fill the gap in the industrial prototyping and early deployment market with a compact form factor, low-cost and robust industrial design. I3Mote is an advanced and compact prototyping system integrating the required components to be deployed as a product, leveraging the need for adopting industries to build their own tailored solution. This article describes the platform design, firmware and software ecosystem and characterizes its performance in terms of energy consumption.

Impact of Prefrontal Theta Burst Stimulation on Clinical Neuropsychological Tasks.

Abstract: Theta burst stimulation (TBS) protocols hold high promise in neuropsychological rehabilitation. Nevertheless, their ability to either decrease (continuous, cTBS) or increase (intermittent, iTBS) cortical excitability in areas other than the primary motor cortex, and their consistency modulating human behaviors with clinically relevant tasks remain to be fully established. The behavioral effects of TBS over the dorsolateral prefrontal cortex (dlPFC) are particularly interesting given its involvement in working memory (WM) and executive functions (EF), often impaired following frontal brain damage. We aimed to explore the ability of cTBS and iTBS to modulate WM and EF in healthy individuals, assessed with clinical neuropsychological tests (Digits Backward, 3-back task, Stroop Test, and Tower of Hanoi). To this end, 36 participants were assessed using the four tests 1 week prior to stimulation and immediately following a single session of either cTBS, iTBS, or sham TBS, delivered to the left dlPFC. No significant differences were found across stimulation conditions in any of the clinical tasks. Nonetheless, in some of them, active stimulation induced significant pre/post performance modulations, which were not found for the sham condition. More specifically, sham stimulation yielded improvements in the 3-back task and the Color, Color-Word, and Interference Score of the Stroop Test, an effect likely caused by task practice. Both, iTBS and cTBS, produced improvements in Digits Backward and impairments in 3-back task accuracy. Moreover, iTBS increased Interference Score in the Stroop Test in spite of the improved word reading and impaired color naming, whereas cTBS decreased the time required to complete the Tower of Hanoi. Differing from TBS outcomes reported for cortico-spinal measures on the primary motor cortex, our analyses did not reveal any of the expected performance differences across stimulation protocols. However, if one considers independently pre/post differences for each individual outcome measure and task, either one or both of the active protocols appeared to modulate WM and EF. We critically discuss the value, potential explanations, and some plausible interpretations for this set of subtle impacts of left dlPFC TBS in humans.

Extracting software product line feature models from natural language specifications

Abstract: The specification of a family of software products may include documents written in natural language. Automatically extracting knowledge from these documents is a challenging problem that requires using Natural Language Processing (NLP) techniques. This knowledge can be formalized as a Feature Model (FM), a diagram capturing the key features and the relationships among them.In this paper, we first review previous works that have presented tools for extracting FMs from textual specifications and compare their strengths and limitations. Then, we propose a framework for feature and relationship extraction, which overcomes the identified limitations and is built upon state-of-the-art open-source NLP tools. This framework is evaluated against previous works using several case studies, showing improved results.

A Dialogic Feedback Index measuring key aspects of feedback processes in online learning environments

Abstract: Research on feedback shows the dialogic perspective as one that potentially promotes learning improvement. This article presents the Dialogic Feedback Index (DFI), a measure that contributes to est...