Abstract
This paper proposes the linear frequency cepstral coefficients as highly discriminative features for anomaly detection in ball bearings using vibration sensor data. These features are based on cepstral analysis and are capable of encoding the patterns of a spectral magnitude profile. Incipient damages on bearings can grow rapidly under normal use resulting in vibration and harsh noise. If left undetected, this damage will worsen, leading to high maintenance costs or even injury. Multiple interferences in an industrial environment contaminate the signal, making it a challenge to correctly identify the bearings' condition. Many studies have attempted to overcome this issue at the signal level. However, the discriminative capacity of the current vibration signal features is still vulnerable to interference, which motivates this work. In order to demonstrate the benefits of these features, we (1) show that they are computationally efficient and suitable for real-time incremental training; (2) conduct discriminative analysis by evaluating the separability performance and comparing it with the state of the art; and (3) test the robustness of the proposed features under noise interference, which is ideal for use in the harsh operating conditions of industrial machinery. The data was obtained from a laboratory workbench setting that reproduces bearing fault scenarios. Results show that the proposed features are fast, competitive when compared to state-of-the-art features, and resilient to high levels of interference. Despite the higher performance when using the quadratic model, the proposed features remain highly discriminative when used with several other discriminant function.

Abstract
Innovation stills on the world's agenda as the holy grail of business success. Nevertheless, it stills hard for some communities to understand and embrace innovation processes in a systematic way as a continuum for regional development. Our stance is that innovation seeds, feeds innovation. That means, innovation won't work in a closed cycle, but rather in an open and cross-entity manner, forming a knowledge-managed regional development ecosystem. Accordingly, this paper describes a knowledge lab, designed as an intel structure to offer knowledge-intensive services towards the regional development of the "Tamega e Sousa" (NUTIII) Region. This knowledge lab aims at complementing the installed dynamics on innovation support and economic stimulus in a knowledge-based innovation management approach.

Abstract
The latest forecasts for the Portuguese tourist industry show that it will represent 16% of the Portuguese GNP very soon and, for 2017, the State Statistical Office registered over 3.5 million guests visiting the North of Portugal and around 7.4 million overnight stays in the region's tourist accommodation, which makes it safe to say that investing in projects that foster a common language in business communication will not only result in tangible financial gains but also in improved multi-cultural and multilingual understanding. Companies need, thus, to communicate seamlessly in a fully internationalised and digital world challenges companies to meet the need to systematise and harmonise language to properly convey meaning, thus promoting successful business undertakings. Such a need, a direct consequence of the phenomenon of globalisation and internationalisation of scientific and technological knowledge, becomes clear in a region with all the necessary elements to anchor sustainable growth, namely the four locations classified as UNESCO's World Heritage sites (Porto's historic center, Alto Douro wine region, Oa Valley Archeological Park and GuimarSes Historic Center). "WiTo - Do you speak wine tourism?" is a project, supported by a PhD thesis, that aims at creating an electronic multilingual thesaurus the wine tourism experts will consider a useful tool for communicating with different publics (experts and non-experts). Thus, we will have to determine which subjects and technical know-how are considered core, complementary and cross-sectional to wine tourism, leading to the conceptual representation of wine tourism specialised language (which, in turn, will allow for structuring and harmonization of the linguistic heritage clearly visible in the area's terminology). This project aims at providing the necessary basis for optimising knowledge transfer (thus promoting a faster flow of technical and scientific information) and its implementation in tourism information systems and electronic support platforms. This article aims at giving an overview of the current research in this area and presenting WiTo by highlighting some of its preliminary results and discussing some of the open questions.

Abstract
This article arises from the proposal of a new approach regarding the inclusion of soft-digital skills training in higher education. The study carried out on several curricular units in different higher education courses in Portugal led us to reflect on a different educational model, which combines the development of soft skills in digital environments. Digitalization and the use of technologies since early ages in the educational process are raising interesting questions. This article intends to go deeper on the use of digital technologies, namely through the virtual environments imposed by higher education institutions as a form of study. The main question is how pedagogies and the use of technologies have a meeting point where it is possible to continue humanization in education through the utilization of virtual environments to support the teaching/learning process. The methodology used in this study has its support on questionnaires made to students of higher education in different areas of knowledge, such as medicine, nursing, engineering, management, arts and literature. The main conclusions of this study are the importance of creating and using digital platforms that not only support the study but also contemplate the use of a virtual reality where students can interact with others in the discussion and resolution of real life situations.

Abstract
Previous literature shows that there are different environmental factors with different impacts on the adoption of technologies in a supply chain context. Thus, the adoption of technologies in supply chains may vary according to different environmental factors. Despite the existence of several studies about adoption of technologies in supply chain contexts that include environmental factors, there is a gap in identifying which environmental factors influence the adoption of digitalization technologies in supply chains. The purpose of this study is therefore to identify and analyze the environmental factors that influence the adoption of digitalization technologies in the supply chain. An exploratory qualitative research was conducted using semi-structured interviews with Portuguese managers of companies at several tiers of the automotive supply chain. Environmental factors were pointed as particularly critical drivers to promote the adoption of digitalization technologies in the automotive supply chain. Such adoption is mainly driven by the Original Equipment Manufacturer ( OEM), through coercive and normative pressures over the other tiers of the supply chain. Relevant factors identified are: compliance with standards and legislation, market and industry pressures, and benchmark the evolution of supply chain partners. This study contributes to the literature with new knowledge concerning new specificities of the environmental factors that showed an important influence on the adoption decision.

Abstract
In IEEE 802.11 based wireless networks interference increases as more access points are added. A metric helping to quantize this interference seems to be of high interest. In this paper we study the relationship between the improved attacking case metric, which captures interference, and throughput for IEEE 802.11 based network using directional antenna. The y(1/3) = a + b (ln x)(3) model was found to best represent the relationship between the interference metric and the network throughput. We use this model to predict the performance of similar networks and decide the best configuration a network operator could use for planning his network.