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Publications

2018

Do software startups innovate in the same way? A case survey study

Authors
Melegati, J; Wang, X;

Publication
SiBW

Abstract
The research interest in software startups has expanded a lot in the last years as shown by the increase in the published papers, and the organization of research workshops. However, two recent systematic mapping studies recognize an inconsistency in the characterization of software startups in the literature, even though they acknowledge that innovativeness and uncertainty are the common themes the literature uses to describe these companies. In the new product development literature, even though not consolidated, innovativeness is usually related to technology and/or market discontinuities. These two different types of novelty could bring distinct consequences to software development activities in software startups. Using a case survey research approach, we analyzed 27 published papers from the period 2013-17. We identified and categorized the innovation in 18 software startups products or services from the perspective of discontinuities. We found that software engineering literature did not differentiate software startups based on the innovations they develop. Nevertheless, most studied software startups work on products with a market discontinuity and without a technological one.

2018

Immersive Edition of Multisensory 360 Videos

Authors
Coelho, H; Melo, M; Barbosa, L; Martins, J; Teixeira, MS; Bessa, M;

Publication
WorldCIST (2)

Abstract
The current technologic proliferation has originated new paradigms concerning the production and consumption of multimedia content. This paper proposes a multisensory 360 video editor that allows producers to edit such contents with high levels of customization. This authoring tool allows the edition and visualization of 360 video with the novelty of allowing to complement the 360 video with multiple stimuli such as audio, haptics, and olfactory. In addition to this multisensory feature, the authoring tool allows customizing individually each of the stimuli to provide an optimal multisensory user experience. A usability evaluation has revealed the pertinence of the editor, where it was verified an effectiveness rate of 100%, only one help request out of 10 participants, and positive efficiency. Satisfaction-wise, results equally revealed high level of satisfaction as the average score was 8.3 out of 10.

2018

Context-aware tourism technologies

Authors
Leal, F; Malheiro, B; Burguillo, JC;

Publication
KNOWLEDGE ENGINEERING REVIEW

Abstract
Nowadays travellers can benefit from the computing capabilities, collection of on board sensors and ubiquitous Internet access provided by mobile devices. These are the three pillars of any tourist support system since they provide the power, means and data to establish the local user context, to access remote services and to provide value-added user-centred context-aware applications. However, making sense of the user context data is not straightforward, as it requires dedicated knowledge acquisition and knowledge representation solutions. Besides, the range and diversity of available data sources is huge, requiring appropriate knowledge processing techniques to provide addequated tourism services. This article presents an updated review, and a comparison of recent context-aware tourism applications (CATA), including supporting technologies; and considering four possible dimensions: knowledge acquisition, knowledge representation, knowledge processing and knowledge-based services. We propose and apply a CATA analysis framework, contemplating these four dimensions to the applications found in the literature. This survey constitutes, not only, a state of the art review on tourism mobile applications, but, also, anticipates the latest development trends in tourism-related applications.

2018

Deep Image Segmentation by Quality Inference

Authors
Fernandes, K; Cruz, R; Cardoso, JS;

Publication
2018 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)

Abstract
Traditionally, convolutional neural networks are trained for semantic segmentation by having an image given as input and the segmented mask as output. In this work, we propose a neural network trained by being given an image and mask pair, with the output being the quality of that pairing. The segmentation is then created afterwards through backpropagation on the mask. This allows enriching training with semi-supervised synthetic variations on the ground-truth. The proposed iterative segmentation technique allows improving an existing segmentation or creating one from scratch. We compare the performance of the proposed methodology with state-of-the-art deep architectures for image segmentation and achieve competitive results, being able to improve their segmentations.

2018

Consumo de Canábis: craving e a relação com ansiedade, stresse e depressão

Authors
Vasconcelos-Raposo, J; Couto, S; Formiga, N; Teixeira, CM;

Publication
Actualidades en Psicología

Abstract
A canábis é a substância ilícita mais consumida em Portugal com um início de consumo muito precoce. O craving é considerado um dos factores fundamentais ligados ao consumo de canábis, associando-se à depressão, a ansiedade e ao stresse. Espera-se que nível de craving e sexo se relacionem com a depressão, ansiedade e stresse numa amostra de consumidores portugueses. A amostra foi constituída por 143 consumidores da zona Norte do país e os dados recolhidos através de questionários online (DASS-21 e o MCQ-SF). Os resultados permitem concluir que a emocionalidade, a intencionalidade e a compulsividade relacionaram-se positivamente com o nível do craving, bem como, com o stresse e a depressão. Quanto ao número de anos de consumo, constatou-se um efeito significativo, de dimensão média, na ansiedade.

2018

An indoor navigation architecture using variable data sources for blind and visually impaired persons

Authors
Gomes, JP; Sousa, JP; Cunha, CR; Morais, EP;

Publication
2018 13TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI)

Abstract
Contrary to outdoor positioning and navigation systems, there isn't a counterpart global solution for indoor environments. Usually, the deployment of an indoor positioning system must be adapted case by case, according to the infrastructure and the objective of the localization. A particularly delicate case is related with persons who are blind or visually impaired. A robust and easy to use indoor navigation solution would be extremely useful, but this would also be particularly difficult to develop, given the special requirements of the system that would have to be more accurate and user friendly than a general solution This paper presents a contribute to this subject, by proposing a hybrid indoor positioning system adaptable to the surrounding indoor structure, and dealing with different types of signals to increase accuracy. This would permit lower the deployment costs, since it could be done gradually, beginning with the likely existing Wi-Fi infrastructure to get a fairy accuracy up to a high accuracy using visual tags and NFC tags when necessary and possible.

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