2022
Authors
Moreira, J; Castanheira, F; Mendes, D; Gonçalves, D;
Publication
PROCEEDINGS OF THE 17TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (IVAPP), VOL 3
Abstract
Visualizations for Streaming Big Data need to handle high volumes of information in real-time, making it challenging to convey significant data changes without confusing users. A simple first approach would be switching from the current visual idiom to another, highlighting a significant change. Unfortunately, there are no guidelines to design effective transitions between two visual idioms in Streaming Big Data. Therefore, we created a tree of animation concepts to serve as a starting point for designing such animated transitions. The concepts represent several ways in which a visual idiom can be transformed into another. We chose three visual idioms to test our idea and arranged several concepts to apply at each possible pairing (six possibilities). For each pairing, we tested the accuracy of people's perceptions. Finally, we conducted a user study with 100 participants, where each participant answered various questions about transitions between two visual idioms shown in several videos. We concluded that to conceive appropriate animated transitions for Streaming Big Data (which also applies just for Data Streaming) that allow users to understand the changes in incoming data, varying how the proposed concepts are applied is not enough, highlighting the need for future research to address this challenge.
2022
Authors
Silva, PA; Magalhaes, LG; Mendes, D; Giachetti, A;
Publication
COMPUTERS & GRAPHICS-UK
Abstract
2022
Authors
Almeida, F; Simões, J; Lopes, S;
Publication
Future Internet
Abstract
The combined adoption of Agile and DevOps enables organizations to cope with the increasing complexity of managing customer requirements and requests. It fosters the emergence of a more collaborative and Agile framework to replace the waterfall models applied to software development flow and the separation of development teams from operations. This study aims to explore the benefits of the combined adoption of both models. A qualitative methodology is adopted by including twelve case studies from international software engineering companies. Thematic analysis is employed in identifying the benefits of the combined adoption of both paradigms. The findings reveal the existence of twelve benefits, highlighting the automation of processes, improved communication between teams, and reduction in time to market through process integration and shorter software delivery cycles. Although they address different goals and challenges, the Agile and DevOps paradigms when properly combined and aligned can offer relevant benefits to organizations. The novelty of this study lies in the systematization of the benefits of the combined adoption of Agile and DevOps considering multiple perspectives of the software engineering business environment.
2022
Authors
Lopes, SFSF; Simões, JMdAP;
Publication
Online Distance Learning Course Design and Multimedia in E-Learning - Advances in Mobile and Distance Learning
Abstract
2022
Authors
Morais, J; Simões, J; Lourenço, J; Sargo, S;
Publication
Revista EDaPECI
Abstract
2022
Authors
Sequeiros, JA; Silva, R; Santos, AS; Bastos, J; Varela, MLR; Madureira, AM;
Publication
INNOVATIONS IN INDUSTRIAL ENGINEERING
Abstract
There are Optimization Problems that are too complex to be solved efficiently by deterministic methods. For these problems, where deterministic methods have proven to be inefficient, if not completely unusable, it is common to use approximate methods, that is, optimization methods that solve the problems quickly, regardless of their size or complexity, even if they do not guarantee optimal solutions. In other words, methods that find acceptable solutions, efficiently. One particular type of approximate method, which is particularly effective in complex problems, are metaheuristics. Particle Swarm Optimization is a population-based metaheuristic, which has been particularly successful. In order to broaden the application and overcome the limitation of Particle Swarm Optimization, a discrete version of the metaheuristics is proposed. The Discrete Particle Swarm Optimization, DPSO, will change the PSO algorithm so it can be applied to discrete optimization problems. This alteration will focus on the velocity update equation. The DPSO was tested in an instance of the Traveling Salesman Problem, att48, 48 points problems proposed by Padberg and Rinaldi, which showed some promising results.
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