Best practices of international double degree programmes. Case of Russian and European universities

The purpose of the Master’s thesis research is to study and disseminate the best practices of international double Master’s degree programmes organization, implementation and development. The given research is focused on two main areas: motivation of higher education institutions to start double degree programmes and best practices of double degree programme design and implementation from the perspective of building joint curriculum and organizing balanced mobility and development of existing programmes in terms of increasing their quality and attractiveness. This is a case study of the double degree programmes between Russian and European universities. The study findings reveal good developments in the field of double degree cooperation between Russian and European universities and a high motivation from both parties. The research depicts different models of building a joint curriculum and organizing academic mobility. The following areas could be outlined as development points for double degree programmes: - Personal interest and commitment of organizers of double degree programmes; - Comprehensive agreement between partners on different aspects and practicalities of the double degree programme implementation; - Promotion towards more balanced student participation and two-way mobility; - Foreign language skills improvement for students and university staff; - Joint strategy and actions in marketing and quality assurance; - Involvement of international companies; - Wider usage of e-learning technology.

Tracing Innovation Practices in Seaports: the Ports of Klaipeda and Stockholm as Case Studies

This study explores variegated means through which ports have become increasingly entangled in the planning logic of neoliberal innovation-driven economy. The research topic belongs to the academic disciplines of economics and human geography. The aim of the thesis is to analyse how the notion of innovation, adopted in a variety of supranational and national port policy documents, is deployed in operational port environment in two different ports of the Baltic Sea Region: the port of Stockholm, Sweden, and the port of Klaipeda, Lithuania. This novel innovation agenda is visible in several topics I examine in the study, that is, port governance, environmental issues, and seaport – port-city interface. The gathered primary source material on port policy documents, strategies, development planning documents and reports is analysed by utilizing the qualitative content analysis research method. Moreover, the empirical part of the case study, that is, tracing innovation practices in mundane port activities is based on collected qualitative semi-structured interviews with port authorities in Klaipeda and Stockholm, researchers and other port experts. I examine the interview material by employing the theoretical reading research method. In my analysis, I have reframed port-related policy development by tracing and identifying the port transformation from “functional terminals” to “engines for growth”. My results show that this novel innovation-oriented rhetoric imprinted in the narrative “engines for growth” is often contested in daily port practices. In other words, my analysis reveals that the port authorities’ and other port actors’ attitudes towards innovations do not necessarily correspond to the new narrative of innovation and do not always “fit” within a framework of neoliberal economic thinking that glorifies the “culture of innovations”. I argue that the ability to develop innovative initiatives in the ports of Klaipeda and Stockholm is strongly predetermined by local conditions, a port’s governance model, the way port actors perceive the importance of innovations per se, demand factors and new regulations.

Spectral Analysis of Symmetric and Anti-Symmetric Pairwise Kernels

This work investigates theoretical properties of symmetric and anti-symmetric kernels. First chapters give an overview of the theory of kernels used in supervised machine learning. Central focus is on the regularized least squares algorithm, which is motivated as a problem of function reconstruction through an abstract inverse problem. Brief review of reproducing kernel Hilbert spaces shows how kernels define an implicit hypothesis space with multiple equivalent characterizations and how this space may be modified by incorporating prior knowledge. Mathematical results of the abstract inverse problem, in particular spectral properties, pseudoinverse and regularization are recollected and then specialized to kernels. Symmetric and anti-symmetric kernels are applied in relation learning problems which incorporate prior knowledge that the relation is symmetric or anti-symmetric, respectively. Theoretical properties of these kernels are proved in a draft this thesis is based on and comprehensively referenced here. These proofs show that these kernels can be guaranteed to learn only symmetric or anti-symmetric relations, and they can learn any relations relative to the original kernel modified to learn only symmetric or anti-symmetric parts. Further results prove spectral properties of these kernels, central result being a simple inequality for the the trace of the estimator, also called the effective dimension. This quantity is used in learning bounds to guarantee smaller variance.