On trust, knowledge, sharing and innovation

Organisations continuously innovate, create, and are competitive if they improve their performance through continuous intellectual capital development, a key resource for value creation and organisational performance driver. Apart from sustaining competitive advantage, intellectual capital is increasingly important due to its ability to increase shareholder value, especially in public organisations. Employee learning, talent development, and knowledge creation allow the organisation to generate innovative ideas due to the quickness of knowledge obsolescence. The organisation's dynamic capabilities create and re-ignite organisational competencies for business sustainability being co-ordinated by well-structured organisational strategic routines ensuring continuous value creation streams into the business. This chapter focuses on the relationship between notions of knowledge sharing and trust in organisations. Lack of trust can impact negatively organisational knowledge sharing, dependent on trust, openness, and communication. The research sample included graduates and postgraduate students from two universities in Portugal. The findings revealed different perceptions according to the age group.

ADSNARK: Nearly practical and privacy-preserving proofs on authenticated data

We study the problem of privacy-preserving proofs on authenticated data, where a party receives data from a trusted source and is requested to prove computations over the data to third parties in a correct and private way, i.e., the third party learns no information on the data but is still assured that the claimed proof is valid. Our work particularly focuses on the challenging requirement that the third party should be able to verify the validity with respect to the specific data authenticated by the source — even without having access to that source. This problem is motivated by various scenarios emerging from several application areas such as wearable computing, smart metering, or general business-to-business interactions. Furthermore, these applications also demand any meaningful solution to satisfy additional properties related to usability and scalability. In this paper, we formalize the above three-party model, discuss concrete application scenarios, and then we design, build, and evaluate ADSNARK, a nearly practical system for proving arbitrary computations over authenticated data in a privacy-preserving manner. ADSNARK improves significantly over state-of-the-art solutions for this model. For instance, compared to corresponding solutions based on Pinocchio (Oakland’13), ADSNARK achieves up to 25× improvement in proof-computation time and a 20× reduction in prover storage space.

Development of an intelligent earthwork optimization system

Tese de Doutoramento em Engenharia Civil.

DNA evidence collecting in criminal investigation: Portuguese and Thai legal approaches

Doctoral Thesis in Juridical Sciences (Specialty in Public Legal Sciences)

Relative information entropy in cosmology: The problem of information entanglement

The necessary information to distinguish a local inhomogeneous mass density field from its spatial average on a compact domain of the universe can be measured by relative information entropy. The Kullback-Leibler (KL) formula arises very naturally in this context, however, it provides a very complicated way to compute the mutual information between spatially separated but causally connected regions of the universe in a realistic, inhomogeneous model. To circumvent this issue, by considering a parametric extension of the KL measure, we develop a simple model to describe the mutual information which is entangled via the gravitational field equations. We show that the Tsallis relative entropy can be a good approximation in the case of small inhomogeneities, and for measuring the independent relative information inside the domain, we propose the R\'enyi relative entropy formula.