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AbstractThousands of Roma were killed in Ukraine by the Nazis and auxiliary police on the spot. There are more than 50,000 Roma in today’s Ukraine, represented by second and third generation decendants of the genocide survivors. The discussion on Roma identity cannot be isolated from the memory of the genocide, which makes the struggle over the past a reflexive landmark that mobilizes the Roma movement. About twenty Roma genocide memorials have been erected in Ukraine during last decade, and in 2016 the national memorial of the Roma genocide was opened in Babi Yar. However, scholars do not have a clear picture of memory narratives and memory practices of the Roma genocide in Ukraine. A comprehensive analysis of the contemporary situation is not possible without an examination of the history and memory of the Roma genocide before 1991.

2 uppl. 2015

Recently rediscovered photographs of the remains of thirteen individuals buried in the Sado Valley Mesolithic shell middens of Poças de S. Bento and Arapouco, excavated in 1960 and 1962, show the potential of revisiting excavation archives with new methods. The analysis, which applies the principles of archaeothanatology and is enriched by experimental taphonomic research, confirmed details concerning the treatment of the dead body and provided new insights into the use of burial spaces. Some bodies may have been mummified prior to burial, a phenomenon possibly linked to their curation and transport, highlighting the significance of both the body and the burial place in Mesolithic south-western Portugal.

A neural language model trained on a text corpus can be used to induce distributed representations of words, such that similar words end up with similar representations. If the corpus is multilingual, the same model can be used to learn distributed representations of languages, such that similar languages end up with similar representations. We show that this holds even when the multilingual corpus has been translated into English, by picking up the faint signal left by the source languages. However, just as it is a thorny problem to separate semantic from syntactic similarity in word representations, it is not obvious what type of similarity is captured by language representations. We investigate correlations and causal relationships between language representations learned from translations on one hand, and genetic, geographical, and several levels of structural similarity between languages on the other. Of these, structural similarity is found to correlate most strongly with language representation similarity, whereas genetic relationships—a convenient benchmark used for evaluation in previous work—appears to be a confounding factor. Apart from implications about translation effects, we see this more generally as a case where NLP and linguistic typology can interact and benefit one another.

Hemligstämpla eller utplåna? Arkivbildningen och den personliga integriteten i Sverige 1900–2015

By examining the donations by the local nobility to the local church, this thesis aims to study the church as a public room. By analyzing the donations of the nobility in relation to Habermas concept of the public sphere and the concept of conspicuous consumption the donations to the churches can be viewed as manifestations of power. This thesis studies all donations to the churches that leaves material and visual remnants in the church room. The results shows that there was a conscious strategy for the nobility to use the church for manifestation and representation of power. The nobility used their donations to manifest their power and to represent the power towards the people. This was done by filling the church with their names and coats of arms. By donating liturgical objects, church silver, chapels and coats of arms used for funerals the nobility was able to symbolically place themselves in the religious rituals. The church as a room was a symbolically and hierarchical place, and by connecting themselves with this room by donations the nobility could manifest their position in society, both locally and nationally. 

Uppgifter för behandling av naturliga språk (NLP) har under de senaste åren visat sig vara särskilt effektiva när man använder förtränade språkmodeller som BERT. Det enorma kravet på datorresurser som krävs för att träna sådana modeller gör det dock svårt att använda dem i verkligheten. För att lösa detta problem har komprimeringsmetoder utvecklats. I det här projektet studeras, genomförs och testas några av dessa metoder för komprimering av neurala nätverk för textbearbetning. I vårt fall var den mest effektiva metoden Knowledge Distillation, som består i att överföra kunskap från ett stort neuralt nätverk, som kallas läraren, till ett litet neuralt nätverk, som kallas eleven. Det finns flera varianter av detta tillvägagångssätt, som skiljer sig åt i komplexitet. Vi kommer att titta på två av dem i det här projektet. Den första gör det möjligt att överföra kunskap mellan ett neuralt nätverk och en mindre dubbelriktad LSTM, genom att endast använda resultatet från den större modellen. Och en andra, mer komplex metod som uppmuntrar elevmodellen att också lära sig av lärarmodellens mellanliggande lager för att utvinna kunskap. Det slutliga målet med detta projekt är att ge företagets datavetare färdiga komprimeringsmetoder för framtida projekt som kräver användning av djupa neurala nätverk för NLP. Natural language processing (NLP) tasks have proven to be particularly effective when using pre-trained language models such as BERT. However, the enormous demand on computational resources required to train such models makes their use in the real world difficult. To overcome this problem, compression methods have emerged in recent years. In this project, some of these neural network compression approaches for text processing are studied, implemented and tested. In our case, the most efficient method was Knowledge Distillation, which consists in transmitting knowledge from a large neural network, called teacher, to a small neural network, called student. There are several variants of this approach, which differ in their complexity. We will see two of them in this project, the first one which allows a knowledge transfer between any neural network and another smaller bidirectional LSTM, using only the output of the larger model. And a second, more complex approach that encourages the student model to also learn from the intermediate layers of the teacher model for incremental knowledge extraction. The ultimate goal of this project is to provide the company’s data scientists with ready-to-use compression methods for their future projects requiring the use of deep neural networks for NLP. 

Iron ore mining in the Norrbotten region of Sweden began in the early years of the twentieth century as a commercially uncertain and even dangerous proposition. But even before it began to generate profits, public debate began over the appropriate role of the state and of private capital (including foreign investors). This included whether iron ore should be exported for profit or retained for future processing in Sweden—even though the technology and infrastructure for such domestic industry did not exist. Tracing the evolution of this debate in the Swedish news media through to the First World War, this paper argues that the revenue generated by exports became more attractive than the promise of future domestic industry because that revenue could underwrite pressing political objectives. Although domestic iron ore processing remained linked to visions of future industrial prosperity, uncertain visions of future prosperity lost appeal as the capacity for export revenues to generate prosperity in the present became more potent.