2019
Authors
Almeida, FL; Simões, J;
Publication
Int. J. Serv. Sci. Manag. Eng. Technol.
Abstract
This study investigates the main motivations, difficulties and good practices in the migration process of software development models from Waterfall to Agile experienced by IT Portuguese companies. For that, we adopted a quantitative methodology based on multiple case studies that allowed us to explore five research questions. In a first step, we propose to identify the main reasons that motivate the companies to adopt Agile development processes and we intend to characterize this migration process. We also explore a set of good practices that can be followed in this migration process and we suggest a set of measures that can be used to assess the success of projects in an Agile environment. Finally, we explore the organizational and management impacts with the introduction of Agile processes. Copyright © 2019, IGI Global.
2019
Authors
Almeida, F; Simões, J;
Publication
Advances in Marketing, Customer Relationship Management, and E-Services - Advanced Methodologies and Technologies in Digital Marketing and Entrepreneurship
Abstract
2019
Authors
Essenfelder, R; Canavilhas, J; Maia, HC; Pinto, RJ;
Publication
DOXA COMUNICACION
Abstract
Technological advancements have created a media ecosystem in which traditional journalism sees its existence strongly threatened by the emergence of new players. Social networks have created a competitive environment that, whether due to its dispersion or its capillarity, has relegated the mainstream media to a secondary role in the media ecosystem. Ironically, the technologies that threaten traditional journalism are also those that can save it; provided they are used correctly. Journalism, weakened by the economic crisis and with increasingly smaller newsrooms, has artificial intelligence as an opportunity to recover a certain centrality in the media ecosystem. This paper studies AIDA, a project from the Brazilian television network Globo. This project looked to automation as a way to avoid errors and ambiguities in the news. The study of the AIDA case, complemented by interviews, presents the challenges to achieve the automatization of news regarding electoral polls.
2019
Authors
Vieira, F; Oliveira, E; Rodrigues, N;
Publication
2019 IEEE 7th International Conference on Serious Games and Applications for Health, SeGAH 2019
Abstract
This paper describes the research, development and evaluation process of a solution based on computer vision for the detection and prevention of Computer Vision Syndrome, a type of eye fatigue characterized by the appearance of ocular symptoms during or after prolonged periods watching digital screens. The system developed targets users of computers and mobile devices, detecting and warning users to the occurrence of eye fatigue situations and suggesting corrective behaviours in order to prevent more complicated health consequences. The implementation resorts to machine learning techniques, using eye images datasets for training the eye state detection algorithm. OpenCV Lib was used for eye's segmentation and subsequent fatigue analysis. The final goal of the system is to provide users and health professionals with quality data analysis of eye fatigue levels, in order to raise awareness over accumulated stress and promote behaviour change. © 2019 IEEE.
2019
Authors
Rodrigues, N; Torres, H; Oliveira, B; Borges, J; Queiros, S; Mendes, J; Fonseca, J; Coelho, V; Brito, JH;
Publication
PROCEEDINGS OF THE 14TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISAPP), VOL 5
Abstract
In this paper, a method for estimation of human pose is proposed, making use of ToF (Time of Flight) cameras. For this, a YOLO based object detection method was used, to develop a top-down method. In the first stage, a network was developed to detect people in the image. In the second stage, a network was developed to estimate the joints of each person, using the image result from the first stage. We show that a deep learning network trained from scratch with ToF images yields better results than taking a deep neural network pretrained on RGB data and retraining it with ToF data. We also show that a top-down detector, with a person detector and a joint detector works better than detecting the body joints over the entire image.
2019
Authors
Morais, P; Queiros, S; Pereira, C; Moreira, AHJ; Baptista, MJ; Rodrigues, NF; D'hooge, J; Barbosa, D; Vilaca, JL;
Publication
MEDICAL IMAGING 2019: IMAGE PROCESSING
Abstract
The fusion of pre-operative 3D magnetic resonance (MR) images with real-time 3D ultrasound (US) images can be the most beneficial way to guide minimally invasive cardiovascular interventions without radiation. Previously, we addressed this topic through a strategy to segment the left ventricle (LV) on interventional 3D US data using a personalized shape prior obtained from a pre-operative MR scan. Nevertheless, this approach was semi-automatic, requiring a manual alignment between US and MR image coordinate systems. In this paper, we present a novel solution to automate the abovementioned pipeline. In this sense, a method to automatically detect the right ventricular (RV) insertion point on the US data was developed, which is subsequently combined with pre-operative annotations of the RV position in the MR volume, therefore allowing an automatic alignment of their coordinate systems. Moreover, a novel strategy to ensure a correct temporal synchronization of the US and MR models is applied. Finally, a full evaluation of the proposed automatic pipeline is performed. The proposed automatic framework was tested in a clinical database with 24 patients containing both MR and US scans. A similar performance between the proposed and the previous semi-automatic version was found in terms of relevant clinical measurements. Additionally, the automatic strategy to detect the RV insertion point showed its effectiveness, with a good agreement against manually identified landmarks. Overall, the proposed automatic method showed high feasibility and a performance similar to the semi-automatic version, reinforcing its potential for normal clinical routine.
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