2019
Autores
Kowalewska, G; Niezurawska-Zajac, J; Duarte, N;
Publicação
Olsztyn Economic Journal
Abstract
2019
Autores
He, H; Li, SC; Hu, L; Duarte, N; Manta, O; Yue, XG;
Publicação
SUSTAINABILITY
Abstract
In order to investigate the factors influencing the sustainable guarantee network and its differences in different spatial and temporal scales, logistic regression algorithm is used to analyze the data of listed companies in 31 provinces, municipalities and autonomous regions in China from 2008 to 2017 (excluding Hong Kong, Macau and Taiwan). The study finds that, overall, companies with better profitability, poor solvency, poor operational capability and higher levels of economic development are more likely to join the guarantee network. On the temporal scale, solvency and regional economic development exert increasing higher impact on the companies' accession to the guarantee network, and operational capacity has increasingly smaller impact. On the spatial scale, the less close link between company executives and companies in the western region suggests higher possibility to join the guarantee network. The predictive accuracy test results of the logistic regression algorithm show that the training model of the western sample enterprises has the highest prediction accuracy when predicting enterprise behavior of joining the guarantee network, while the accuracy is the lowest in the central region. When forecasting enterprises' failure to join the guarantee network, the training model of the central sample enterprise has the highest accuracy, while the accuracy is the lowest in the eastern region. This paper discusses the internal and external factors influencing the guarantee network risk from the perspective of spatial and temporal differences of the guarantee network, and discriminates the prediction accuracy of the training model, which means certain guiding significance for listed company management, bank and government to identify and control the guarantee network risk.
2019
Autores
Novais, P; Jung, JJ; Villarrubia, G; Fernández Caballero, A; Navarro, E; González, P; Carneiro, D; Pinto, A; Campbell, AT; Duraes, D;
Publicação
Advances in Intelligent Systems and Computing
Abstract
2019
Autores
Rocha, R; Carneiro, D; Costa, R; Analide, C;
Publicação
Ambient Intelligence - Software and Applications -,10th International Symposium on Ambient Intelligence, ISAmI 2019, Ávila, Spain, 26-28 June 2019.
Abstract
In recent years, the development and use of mobile devices such as smartphones and tablets grew significantly. They are used for virtually every activity of our lives, from communication or online shopping to e-banking or gaming, just to name a few. As a consequence, these devices contribute significantly to make our lives more digital, with all the perks and risks that this encompasses. One of the most serious risk is that of an authorized individual gaining physical access to our mobile device and, potentially, to all the applications and personal data it contains. Most of mobile devices are protected using some kind of password, that can be easily spotted by unauthorized users or event guessed. In the last years, new authentication mechanisms have been proposed, such as those using traditional biometrics or behavioral biometrics. In this paper we propose a new continuous authentication mechanism for mobile devices based on behavioral biometrics that monitors user interaction behavior for classifying the identity of the user. © Springer Nature Switzerland AG 2020.
2019
Autores
Rocha, R; Carneiro, D; Novais, P;
Publicação
PROGRESS IN ARTIFICIAL INTELLIGENCE, PT II
Abstract
Touch screens are nowadays one of the major interfaces in the interaction between humans and technology, mostly due to the significant growth in the use of smartphones and tablets in the last years. This broad use, that reaches people from all strata of society, makes touch screens a relevant tool to study the mechanisms that influence the way we interact with electronic devices. In this paper we collect data regarding the interaction patterns of different users with mobile devices. We present a way to formalize these interaction patterns and analyze how aspects such as age and gender influence them. The results of this research may be relevant for developing mobile applications that identify and adapt to the users or their characteristics, including impairments in fine motor skills or in cognitive function.
2019
Autores
Carneiro, D; Novais, P; Augusto, JC; Payne, N;
Publicação
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
Abstract
The topic of stress is nowadays a very important one, not only in research but on social life in general. People are increasingly aware of this problem and its consequences at several levels: health, social life, work, quality of life, etc. This resulted in a significant increase in the search for devices and applications to measure and manage stress in real-time. Recent technological and scientific evolution fosters this interest with the development of new methods and approaches. In this paper we survey these new methods for stress assessment, focusing especially on those that are suited for the workplace: one of today's major sources of stress. We contrast them with more traditional methods and compare them between themselves, evaluating nine characteristics. Given the diversity of methods that exist nowadays, this work facilitates the stakeholders' decision towards which one to use, based on how much their organization values aspects such as privacy, accuracy, cost-effectiveness or intrusiveness.
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