The European challenge of KMN and innovation: a skills and competence portfolio for knowledge worker in SME's

Versão editor: http://www.isegi.unl.pt/docentes/acorreia/documentos/European_Challenge_KM_Innovation_2004.pdf

The darmstadt challenge (the turing test revisited)

Significant work has been done in the areas of Pervcomp/Ubicomp Smart Environments with advances on making proactive systems, but those advances have not made these type of systems accurately proactive. On the other hand a great deal is needed to make systems more sensible/sensitive and trustable (both in terms of reliability and privacy). We put forward the thesis that a more integral and social-aware sort of intelligence is needed to effectively interact, decide and act on behalf of people’s interest and that a way to test how effective systems are achieving these desirable behaviour is needed as a consequence. We support our thesis by providing examples on how to measure effectiveness in variety of different environments.

Privatization and government preference in a public Stackelberg leader duopoly

We analyse the relationship between the privatization of a public firm and government preferences for tax revenue in a Stackelberg duopoly with the public firm as the leader. We assume that the government payoff is given by a weighted sum of tax revenue and the sum of consumer and producer surplus. We get that if the government puts a sufficiently larger weight on tax revenue than on the sum of both surpluses, it will not privatize the public firm. In contrast, if the government puts a moderately larger weight on tax revenue than on the sum of both surpluses, it will privatize the public firm.

The European Project Semester at ISEP: the challenge of educating global engineers

Current engineering education challenges require approaches that promote scientific, technical, design and complementary skills while fostering autonomy, innovation and responsibility. The European Project Semester (EPS) at Instituto Superior de Engenharia do Porto (ISEP) (EPS@ISEP) is a one semester project-based learning programme (30 European Credit Transfer Units (ECTU)) for engineering students from diverse scientific backgrounds and nationalities that intends to address these goals. The students, organised in multidisciplinary and multicultural teams, are challenged to solve real multidisciplinary problems during one semester. The EPS package, although on project development (20 ECTU), includes a series of complementary seminars aimed at fostering soft, project-related and engineering transversal skills (10 ECTU). Hence, the students enrolled in this programme improve their transversal skills and learn, together and with the team of supervisors, subjects distinct from their core training. This paper presents the structure, implementation and results of the EPS@ISEP that was created in 2011 to apply the best engineering practices and promote internationalisation and engineering education innovation at ISEP.

Government preference, environmental taxes and privatization

We analyse the relationship between the privatization of a public firm and government preferences for environmental tax revenue. The model that we consider is more general than the one consider in Wang and Wang (2009), in the sense that we put a larger weight in the environment tax revenue than on the other terms of the government's objective function. The model has two stages. In the first stage, the government sets the environmental tax. Then, the firms engage in a Cournot competition, choosing output and pollution abatement levels.

Innovations in technology: a friendly math project and the learning analytics “challenge”

Currently the world around us "reboots" every minute and “staying at the forefront” seems to be a very arduous task. The continuous and “speeded” progress of society requires, from all the actors, a dynamic and efficient attitude both in terms progress monitoring and moving adaptation. With regard to education, no matter how updated we are in relation to the contents, the didactic strategies and technological resources, we are inevitably compelled to adapt to new paradigms and rethink the traditional teaching methods. It is in this context that the contribution of e-learning platforms arises. Here teachers and students have at their disposal new ways to enhance the teaching and learning process, and these platforms are seen, at the present time, as significant virtual teaching and learning supporting environments. This paper presents a Project and attempts to illustrate the potential that new technologies present as a “backing” tool in different stages of teaching and learning at different levels and areas of knowledge, particularly in Mathematics. We intend to promote a constructive discussion moment, exposing our actual perception - that the use of the Learning Management System Moodle, by Higher Education teachers, as supplementary teaching-learning environment for virtual classroom sessions can contribute for greater efficiency and effectiveness of teaching practice and to improve student achievement. Regarding the Learning analytics experience we will present a few results obtained with some assessment Learning Analytics tools, where we profoundly felt that the assessment of students’ performance in online learning environments is a challenging and demanding task.

An automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference

In the last few years the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how good is a voice when the application is a speech based interface. In this paper we present a new automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference. Our study is based on a multi-language database composed by female voices. In the objective performance evaluation the system achieved a 7.3% error rate.