Poster 158: Open-Source Rehabilitation Reference Mobile Web Application: A Novel Approach to Creating Collaborative Resources for Physiatrists in Training

PM&R ◽  
2017 ◽  
Vol 9 ◽  
pp. S182-S183
Author(s):  
George E. Marzloff ◽  
Tariq Z. Rajnarine ◽  
Andrew Abdou ◽  
Anokhi Mehta ◽  
Miguel X. Escalon
2021 ◽  
Vol 13 (3) ◽  
pp. 402
Author(s):  
Pablo Rodríguez-Gonzálvez ◽  
Manuel Rodríguez-Martín

The thermography as a methodology to quantitative data acquisition is not usually addressed in the degrees of university programs. The present manuscript proposes a novel approach for the acquisition of advanced competences in engineering courses associated with the use of thermographic images via free/open-source software solutions. This strategy is established from a research based on the statistical and three-dimensional visualization techniques over thermographic imagery to improve the interpretation and comprehension of the different sources of error affecting the measurements and, thereby, the conclusions and analysis arising from them. The novelty is focused on the detection of non-normalities in thermographic images, which is illustrates in the experimental section. Additionally, the specific workflow for the generation of learning material related with this aim is raised for asynchronous and e-learning programs. These virtual materials can be easily deployed in an institutional learning management system, allowing the students to work with the models by means of free/open-source solutions easily. Subsequently, the present approach will give new tools to improve the application of professional techniques, will improve the students’ critical sense to know how to interpret the uncertainties in thermography using a single thermographic image, therefore they will be better prepared to face future challenges with more critical thinking.


2021 ◽  
Author(s):  
Jason Hunter ◽  
Mark Thyer ◽  
Dmitri Kavetski ◽  
David McInerney

<p>Probabilistic predictions provide crucial information regarding the uncertainty of hydrological predictions, which are a key input for risk-based decision-making. However, they are often excluded from hydrological modelling applications because suitable probabilistic error models can be both challenging to construct and interpret, and the quality of results are often reliant on the objective function used to calibrate the hydrological model.</p><p>We present an open-source R-package and an online web application that achieves the following two aims. Firstly, these resources are easy-to-use and accessible, so that users need not have specialised knowledge in probabilistic modelling to apply them. Secondly, the probabilistic error model that we describe provides high-quality probabilistic predictions for a wide range of commonly-used hydrological objective functions, which it is only able to do by including a new innovation that resolves a long-standing issue relating to model assumptions that previously prevented this broad application.  </p><p>We demonstrate our methods by comparing our new probabilistic error model with an existing reference error model in an empirical case study that uses 54 perennial Australian catchments, the hydrological model GR4J, 8 common objective functions and 4 performance metrics (reliability, precision, volumetric bias and errors in the flow duration curve). The existing reference error model introduces additional flow dependencies into the residual error structure when it is used with most of the study objective functions, which in turn leads to poor-quality probabilistic predictions. In contrast, the new probabilistic error model achieves high-quality probabilistic predictions for all objective functions used in this case study.</p><p>The new probabilistic error model and the open-source software and web application aims to facilitate the adoption of probabilistic predictions in the hydrological modelling community, and to improve the quality of predictions and decisions that are made using those predictions. In particular, our methods can be used to achieve high-quality probabilistic predictions from hydrological models that are calibrated with a wide range of common objective functions.</p>


Author(s):  
Morgan Magnin ◽  
Guillaume Moreau ◽  
Nelle Varoquaux ◽  
Benjamin Vialle ◽  
Karen Reid ◽  
...  

A critical component of the learning process lies in the feedback that students receive on their work that validates their progress, identifies flaws in their thinking, and identifies skills that still need to be learned. Many higher-education institutions have developed an active pedagogy that gives students opportunities for different forms of assessment and feedback. This means that students have numerous lab exercises, assignments, and projects. Both instructors and students thus require effective tools to efficiently manage the submission, assessment, and individualized feedback of students’ work. The open-source web application MarkUs aims at meeting these needs: it facilitates the submission and assessment of students’ work. Students directly submit their work using MarkUs, rather than printing it, or sending it by email. The instructors or teaching assistants use MarkUs’s interface to view the students’ work, annotate it, and fill in a marking rubric. Students use the same interface to read the annotations and learn from the assessment. Managing the students’ submissions and the instructors assessments within a single online system, has led to several positive pedagogical outcomes: the number of late submissions has decreased, the assessment time has been drastically reduced, students can access their results and read the instructor’s feedback immediately after the grading process is completed. Using MarkUs has also significantly reduced the time that instructors spend collecting assignments, creating the marking schemes, passing them on to graders, handling special cases, and returning work to the students. In this paper, we introduce MarkUs’ features, and illustrate their benefits for higher education through our own teaching experiences and that of our colleagues. We also describe an important benefit of the fact that the tool itself is open-source. MarkUs has been developed entirely by students giving them a valuable learning opportunity as they work on a large software system that real users depend on. Virtuous circles indeed arise, with former users of MarkUs becoming developers and then supervisors of further development. We will conclude by drawing perspectives about forthcoming features and use, both technically and pedagogically.


2014 ◽  
Vol 102 (1) ◽  
pp. 69-80 ◽  
Author(s):  
Torregrosa Daniel ◽  
Forcada Mikel L. ◽  
Pérez-Ortiz Juan Antonio

Abstract We present a web-based open-source tool for interactive translation prediction (ITP) and describe its underlying architecture. ITP systems assist human translators by making context-based computer-generated suggestions as they type. Most of the ITP systems in literature are strongly coupled with a statistical machine translation system that is conveniently adapted to provide the suggestions. Our system, however, follows a resource-agnostic approach and suggestions are obtained from any unmodified black-box bilingual resource. This paper reviews our ITP method and describes the architecture of Forecat, a web tool, partly based on the recent technology of web components, that eases the use of our ITP approach in any web application requiring this kind of translation assistance. We also evaluate the performance of our method when using an unmodified Moses-based statistical machine translation system as the bilingual resource.


2016 ◽  
Author(s):  
Stephen G. Gaffney ◽  
Jeffrey P. Townsend

ABSTRACTSummaryPathScore quantifies the level of enrichment of somatic mutations within curated pathways, applying a novel approach that identifies pathways enriched across patients. The application provides several user-friendly, interactive graphic interfaces for data exploration, including tools for comparing pathway effect sizes, significance, gene-set overlap and enrichment differences between projects.Availability and ImplementationWeb application available at pathscore.publichealth.yale.edu. Site implemented in Python and MySQL, with all major browsers supported. Source code available at github.com/sggaffney/pathscore with a GPLv3 [email protected] InformationAdditional documentation can be found at http://pathscore.publichealth.yale.edu/faq.


Author(s):  
Mireilla Bikanga Ada

AbstractThis paper reports an evaluation of a mobile web application, “MyFeedBack”, that can deliver both feedback and marks on assignments to students from their lecturer. It enables them to use any device anywhere, any time to check on, and receive their feedback. It keeps the feedback private to the individual student. It enables and successfully fosters dialogue about the feedback between the students and the educator. Feedback and marks were already being delivered using the institution’s learning environment/management system “Moodle”. The study used a sequential explanatory mixed-method approach. Two hundred thirty-nine (239) participants were reported on their experiences of receiving feedback and divided among several groups: (a) feedback delivered in “Moodle”, (b) formative feedback in “MyFeedBack”, and (c) summative feedback in “MyFeedBack”. Overall, results showed a statistically significant more positive attitude towards “MyFeedBack” than “Moodle”, with the summative assessment subgroup being more positive than the formative subgroup. There was an unprecedented increase in communication and feedback dialogue between the lecturer and the students. Qualitative results enriched and complemented the findings. The paper provides guidelines for an enabling technology for assessment feedback. These offer insight into the extent to which any of the new apps and functionalities that have become available since this study might likely be favourably viewed by learners and help achieve the desired pedagogical outcomes. These include: (1) accessible using any device, making feedback accessible anywhere, anytime; (2) display feedback first (before the grade/mark); (3) enable personalisation of group feedback by the teacher; (4) provide privacy for each student; (5) facilitate dialogue and communication about the feedback; and (6) include a monitoring feature. Three goals already put forward in the literature—(1) making the feedback feel more personal, (2) getting a quicker turnround by making it easier for the teachers to achieve this, and (3) prompting more dialogue between the educators and students—are advanced by this study which shows how they can be supported by software, and that when they are achieved then users strongly approve them.


Transport ◽  
2015 ◽  
Vol 30 (3) ◽  
pp. 320-329 ◽  
Author(s):  
Erik Wilhelm ◽  
Joshua Siegel ◽  
Simon Mayer ◽  
Leyna Sadamori ◽  
Sohan Dsouza ◽  
...  

We present a novel approach to developing a vehicle communication platform consisting of a low-cost, open-source hardware for moving vehicle data to a secure server, a Web Application Programming Interface (API) for the provision of third-party services, and an intuitive user dashboard for access control and service distribution. The CloudThink infrastructure promotes the commoditization of vehicle telematics data by facilitating easier, flexible, and more secure access. It enables drivers to confidently share their vehicle information across multiple applications to improve the transportation experience for all stakeholders, as well as to potentially monetize their data. The foundations for an application ecosystem have been developed which, taken together with the fair value for driving data and low barriers to entry, will drive adoption of CloudThink as the standard method for projecting physical vehicles into the cloud. The application space initially consists of a few fundamental and important applications (vehicle tethering and remote diagnostics, road-safety monitoring, and fuel economy analysis) but as CloudThink begins to gain widespread adoption, the multiplexing of applications on the same data structure and set will accelerate its adoption.


2015 ◽  
Vol 16 (1) ◽  
Author(s):  
Edward Daniel ◽  
Goodluck U. Onwukwe ◽  
Rik K. Wierenga ◽  
Susan E. Quaggin ◽  
Seppo J. Vainio ◽  
...  

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