Brain-Computer Interfaces using Machine Learning

This thesis explores machine learning models for the analysis and classification of electroencephalographic (EEG) signals used in Brain-Computer Interface (BCI) systems. The goal is 1) to develop a system that allows users to control home-automation devices using their mind, and 2) to investigate whether it is possible to achieve this, using low-cost EEG equipment. The thesis includes both a theoretical and a practical part. In the theoretical part, we overview the underlying principles of Brain-Computer Interface systems, as well as, different approaches for the interpretation and the classification of brain signals. We also discuss the emergent launch of low-cost EEG equipment on the market and its use beyond clinical research. We then dive into more technical details that involve signal processing and classification of EEG patterns using machine leaning. Purpose of the practical part is to create a brain-computer interface that will be able to control a smart home environment. As a first step, we investigate the generalizability of different classification methods, conducting a preliminary study on two public datasets of brain encephalographic data. The obtained accuracy level of classification on 9 different subjects was similar and, in some cases, superior to the reported state of the art. Having achieved relatively good offline classification results during our study, we move on to the last part, designing and implementing an online BCI system using Python. Our system consists of three modules. The first module communicates with the MUSE (a low-cost EEG device) to acquire the EEG signals in real time, the second module process those signals using machine learning techniques and trains a learning model. The model is used by the third module, that takes control of cloud-based home automation devices. Experiments using the MUSE resulted in significantly lower classification results and revealed the limitations of the low-cost EEG signal acquisition device for online BCIs

The meta-regulation of European industrial relations: : Power shifts, institutional dynamics and the emergence of regulatory competition among Member States

The article comprises three parts. First, we discuss three key concepts used in our research; namely structural power, European social space and meta-governance. In the second and empirical part of the article, we examine attempts to institute market-enhancing modes of metagovernance. These attempts are exemplified either through the proposal of the Service Directive or through the rulings of the European Court of Justice (ECJ) on the cases of Laval, Viking, Luxemburg and Rüffert. We examine the response of the European Trade Union Confederation (ETUC) to these challenges, and discuss the tensions that arise from these rulings between labour and capital but also between national and European spaces of action. In the third part we put forward an alternative framework which allows us to elucidate the particular form of (emerging) meta-governance of industrial relations in the EU and the challenges that stem for unions within the European social space

Nordic social risk management and the challenge of EU regulation : labour market parity at risk

There has been a long-standing consensus among the employer and employee representatives to decide upon management of social risks in the coordination of labour market institutions in the Nordic countries. This consensus has been built upon the idea of parity in collective bargaining, or labour market parity, which refers to the reciprocal recognition of interests between labour market representatives and to parity-based negotiations and agreements in which a consensus can be reached. In this chapter, we argue that the recent developments within what we call ‘the European social space’ prescribe many challenges for the future of collective bargaining in Nordic countries.We discuss the implications that stem from the creation of competitive markets at the European level to the future of the European industrial relations in general and to the Nordic industrial relations in particular. We conclude the chapter with a reflection on the challenges that competition and market-based principles pose for the Nordic model of social risk-sharing and to the potential attempts to apply the ‘labour market parity’ principle beyond the national levels of action

Family as a Socio-economic Actor in the Political Economy of Welfare

After years of neoliberal restructuring of social welfare families are under pressure to act more strategically in absorbing ever-increasing social risks and costs associated with social reproduction. Against this background, our paper explores family’s agency beyond the realm of care provision. We our theoretical understanding of the family as a socio-economic actor by drawing upon Karl Polanyi’s work on the variety of moral rationalities of different types of economic action (reciprocity, redistribution, autarchy and market exchange) and upon work from the critical realist sociological literature on family as a relational subject. Our chapter puts forward an expanded conceptualization of the family as a collective socio-economic actor that deploys a portfolio of moral ‘rationales’ and practices to enhance its members’ welfare and provide them with social protection against both state and market failures. We highlight the need for a new direction for social policy research on the family that treats the terrain of family’s collective agency as a separate level of analysis, where intersections of class, racial, gender and generational inequalities can be re-imagined in studying how different welfare regimes institutionalize the conditions for families to act as socio-economic agents

Nosokomiale Infektionen bei Leber- und Pankreasresektionen in der chirurgischen Klinik A

Risikofaktoren für eine nosokomiale Infektion (NI) sind weibliches Geschlecht, Alter über 60, die Einweisungsdiagnosen Pankreas- und HCC-Karzinom, Vor-OP, Herz-Kreislauf-Erkrankung, Nikotin und Alkohol-abusus, OP´s des ICPM-Typs 55241 und OP-zeiten ab 450 Minuten. Geringe Risikofaktoren sind Gewicht bzw. BMI, vorhandenes Malignom, DM und OP´s des ICPM-Typs 550121. Pat. mit NI haben durchschnittlich 13,2 Tage längere Liege-zeiten: mit Sepsis (SEP) 9,7 d, Harnwegsinfektion (HWI) 16,2 d, Pneumonie (PNEU) 7,6 d, Katheterinfektion (KAT) 19,2 d, Wundinfekt (WI) 9,3 d, und Mehrinfekt 16,9 d. Die meisten gefundenen Bakterien sind Enterokokken. Bei NI verwendet man doppelt so viele Antibiotika. 2/3 der NI- Pat. haben postoperatives Fieber. Postoperative Leukozytose liegt bei 80% der NI-Pat. vor. Das Risiko einer NI bei pankreasoperierten Pat. liegt bei 51,9%. Vom 02.99-08.99 wurden 34 Pat. Infiziert: WI 52,2%, PNEU 26,5%, KAT 8,8% HWI und SEP je 5,8%. Die Infiziertenquote war 38,1%