Co-creation process and challenges in the conceptualization and development of the edCrumble learning design tool

Co-creation process and challenges in the conceptualization and development of the edCrumble learning design tool

 

Albó L, Hernández-Leo D. Co-creation process and challenges in the conceptualization and development of the edCrumble learning design tool. Joint Proceedings of the 1st Co-Creation in the Design, Development and Implementation of Technology-Enhanced Learning workshop (CC-TEL 2018) and Systems of Assessments for Computational Thinking Learning workshop (TACKLE 2018) co-located with 13th European Conference on Technology Enhanced Learning (ECTEL 2018).

This paper presents the co-creation process followed during the conceptualization, development and evaluation of edCrumble: a learning design (LD) tool which provides an innovative visual representation of the LDs characterized by data analytics with the aim of facilitating the planning, visualization, understanding and reuse of complex LDs. Researchers used several participants’ sources and profiles, different methods (including paper and web-based prototyping, questionnaires, interviews, focus groups, role-play games, sharing activities) and workshop types (isolated vs. long-time). Participatory design workshops and activities are described as well as the challenges encountered during the co-design process with the aim of informing other researchers who are thinking of using co-creation. These challenges include the recruitment and motivation of participants, the management of their expectations, the prioritization of the feedback diversity and a short evaluation of the methods used.

 

 

Open Access at UPF e-repository: http://hdl.handle.net/10230/35405


Preoperative Planning and Simulation Framework for Twin-to-Twin Transfusion Syndrome Fetal Surgery

Preoperative Planning and Simulation Framework for Twin-to-Twin Transfusion Syndrome Fetal Surgery

 

Torrents-Barrena J, López-Velazco R, Masoller N, Valenzuela-Alcaraz B, Gratacós E, Eixarch E, Ceresa M, González Ballester MA. Preoperative Planning and Simulation Framework for Twin-to-Twin Transfusion Syndrome Fetal Surgery. CARE 2018, CLIP 2018, OR 2.0 2018, ISIC 2018: OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis

Twin-to-twin transfusion syndrome (TTTS) is a complication of monochorionic twin pregnancies in which arteriovenous vascular communications in the shared placenta lead to blood transfer between the fetuses. Selective fetoscopic laser photocoagulation of abnormal blood vessel connections has become the most effective treatment. Preoperative planning is thus an essential prerequisite to increase survival rates for severe TTTS. In this work, we present the very first TTTS fetal surgery planning and simulation framework. The placenta is segmented in both magnetic resonance imaging (MRI) and 3D ultrasound (US) via novel 3D convolutional neural networks. Likewise, the umbilical cord is extracted in MRI using 3D convolutional long short-term memory units. The detection of the placenta vascular tree is carried out through a curvature-based corner detector in MRI, and the Modified Spatial Kernelized Fuzzy C-Means with a Markov random field refinement in 3D US. The proposed TTTS planning software integrates all aforementioned algorithms to explore the intrauterine environment by simulating the fetoscope camera, determine the correct entry point, train doctors’ movements ahead of surgery, and consequently, improve the success rate and reduce the operation time. The promising results indicate potential of our TTTS planner and simulator for further assessment on clinical real surgeries.

DOI: https://doi.org/10.1007/978-3-030-01201-4_20


[EEG] The Bern-Barcelona EEG database

[EEG] The Bern-Barcelona EEG database

 

This page provides information about the source code, data, and results provided along with the manuscript [1]. If you use any of these resources, please make sure that you cite reference [1]. This will allow other researchers to locate the resources and the corresponding information. Links to the source code, data, and results can be found at the bottom of this page.  We suggest to refer to the resources as Bern-Barcelona EEG database

[1] Andrzejak RG, Schindler K, Rummel C (2012).  Nonrandomness, nonlinear dependence, and nonstationarity of electroencephalographic recordings from epilepsy patients. Phys. Rev. E, 86, 046206

 
Key wordselectroencephalogram, epilepsy, intracranial EEG recordings, nonlinear signal analysis, nonlinear time series analysis, free EEG database, nonlinear prediction error source code, surrogate signals, surrogate source code, EEG download page Bonn, electroencephalographic recordings, open Matlab source codes

[PhD Thesis] Computational modeling of user activity in full-body interaction environments for ASC children: multimodal analysis of social interaction behaviors through psychophysiology, system activity, video coding, questionnaires, and body cues

[PhD Thesis] Computational modeling of user activity in full-body interaction environments for ASC children: multimodal analysis of social interaction behaviors through psychophysiology, system activity, video coding, questionnaires, and body cues

[PhD Thesis] Computational modeling of user activity in full-body interaction environments for ASC children: multimodal analysis of social interaction behaviors through psychophysiology, system activity, video coding, questionnaires, and body cues

Author: Batuhan Sayis

Supervisor: Narcís Parés, Rafael Ramírez

Full-body Interaction experiences based on Mixed Reality (MR) systems are already playing an important role in encouraging socialization behaviors in children with Autism Spectrum Condition (ASC), as seen in the state of the art of this thesis. However, the data from these systems is multimodal in nature and complex to analyze. Fusion and analysis of this data is crucial to achieve a complete understanding of how these resources interact with each other. In this PhD Thesis, given the characteristics of full-body interaction, we developed new multimodal data gathering and evaluation techniques to better understand the effectiveness of the experience developed in our Full-body Interaction Lab (FuBIntLab) called Lands of Fog. This is a large-scale MR, full-body interaction environment, which allows two children to play face-to-face and explore the physical and virtual worlds simultaneously. Specifically, we developed an experimental setup for comparing Lands of Fog with a control condition based on LEGO construction toys, which includes: recording psychophysiological measures synchronized with other data sources such as observed overt behaviors and system logs of game events. In order to capture accurate psychophysiological data, we developed a wearable that is child-friendly and robust to movement artifacts in the context of ambulatory full-body interaction. In order to integrate observed overt behaviors with other data sources, we designed and developed a novel video coding protocol and an adapted coding grid conceived for Social Interaction Behaviors (SIBs) in ASC children. Using a repeated measure design, we collected data from seventy-two children (36 ASC/non-ASC dyads) from the city of Barcelona, with ages between 8-12 years old (N = 12 female, N = 60 male). Data from these trials has been organized into a public database and processed based on a semi-automatic software pipeline developed within this project. Based on this data we developed three different computational models for modelling SIBs in children with ASC during Lands of Fog sessions, compared to LEGO sessions. The results of this research support the idea that full-body interaction MR environments are capable of fostering SIBs in children with ASC with similar success as the LEGO setting, with an added advantage of being more flexible. Findings reported here shed new light on developing a tool that is mediating, guiding, and supporting the progress of the children in terms of practicing SIBs and providing structure and assistance to therapists.

Link to manuscript: http://hdl.handle.net/10803/671850


[PhD Thesis] Emancipation of the bitcoin outcasts: addressing overlooked elements of the bitcoin network for improving security and efficiency

[PhD Thesis] Emancipation of the bitcoin outcasts: addressing overlooked elements of the bitcoin network for improving security and efficiency

[PhD Thesis] Emancipation of the bitcoin outcasts: addressing overlooked elements of the bitcoin network for improving security and efficiency

Author: Federico Franzoni

Supervisor: Vanesa Daza

During the last decade, cryptocurrencies have revolutionized the financial industry. In these systems, participants communicate by means of a peer-to-peer protocol. Today, many of such protocols take Bitcoin as a reference model, making its study particularly important. This thesis explores some important aspects of the Bitcoin network, related to its security and efficiency, that received limited coverage in research. Firstly, properties of the Testnet network are explored, showing they can be exploited for malicious activities. Secondly, security aspects of an open network topology are studied, arguing against the current obfuscated approach, and designing a viable monitoring system. Then, unreachable nodes are considered, showing their relevance in the network, and proposing changes to the protocol that improve efficiency and security. Finally, a new transaction relay protocol is proposed, which improves anonymity. The results obtained show that the aspects we analyze are not sufficiently covered in research and deserve more deep investigation.

 

Link to manuscript: http://hdl.handle.net/10803/671853