Testing Platform Development for Large Scale Solar Integration

Currently, a high penetration level of Distributed Generations (DGs) has been observed in the Danish distribution systems, and even more DGs are foreseen to be present in the upcoming years. How to utilize them for maintaining the security of the power supply under the emergency situations, has been of great interest for study. This master project is intended to develop a control architecture for studying purposes of distribution systems with large scale integration of solar power. As part of the EcoGrid EU Smart Grid project, it focuses on the system modelling and simulation of a Danish representative LV network located in Bornholm island. Regarding the control architecture, two types of reactive control techniques are implemented and compare. In addition, a network voltage control based on a tap changer transformer is tested. The optimized results after applying a genetic algorithm to five typical Danish domestic loads are lower power losses and voltage deviation using Q(U) control, specially with large consumptions. Finally, a communication and information exchange system is developed with the objective of regulating the reactive power and thereby, the network voltage remotely and real-time. Validation test of the simulated parameters are performed as well.

Testing a large-scale forestry scenario model by means of successive inventories on a forest property

Abstract

Small and Large Scale Dynamics in the Milky Way

This thesis contains dynamical analysis on four different scales: the Solar system, the Sun itself, the Solar neighbourhood, and the central region of the Milky Way galaxy. All of these topics have been handled through methods of potential theory and statistics. The central topic of the thesis is the orbits of stars in the Milky Way. An introduction into the general structure of the Milky Way is presented, with an emphasis on the evolution of the observed value for the scale-length of the Milky Way disc and the observations of two separate bars in the Milky Way. The basics of potential theory are also presented, as well as a developed potential model for the Milky Way. An implementation of the backwards restricted integration method is shown, rounding off the basic principles used in the dynamical studies of this thesis. The thesis looks at the orbit of the Sun, and its impact on the Oort cloud comets (Paper IV), showing that there is a clear link between these two dynamical systems. The statistical atypicalness of the orbit of the Sun is questioned (Paper I), concluding that there is some statistical typicalness to the orbit of the Sun, although it is not very significant. This does depend slightly on whether one includes a bar, or not, as a bar has a clear effect on the dynamical features seen in the Solar neighbourhood (Paper III). This method can be used to find the possible properties of a bar. Finally, we look at the effect of a bar on a statistical system in the Milky Way, seeing that there are not only interesting effects depending on the mass and size of the bar, but also how bars can capture disc stars (Paper II).

Optimization and Applications of Large-Scale Biomedical Event Networks

The overwhelming amount and unprecedented speed of publication in the biomedical domain make it difficult for life science researchers to acquire and maintain a broad view of the field and gather all information that would be relevant for their research. As a response to this problem, the BioNLP (Biomedical Natural Language Processing) community of researches has emerged and strives to assist life science researchers by developing modern natural language processing (NLP), information extraction (IE) and information retrieval (IR) methods that can be applied at large-scale, to scan the whole publicly available biomedical literature and extract and aggregate the information found within, while automatically normalizing the variability of natural language statements. Among different tasks, biomedical event extraction has received much attention within BioNLP community recently. Biomedical event extraction constitutes the identification of biological processes and interactions described in biomedical literature, and their representation as a set of recursive event structures. The 2009–2013 series of BioNLP Shared Tasks on Event Extraction have given raise to a number of event extraction systems, several of which have been applied at a large scale (the full set of PubMed abstracts and PubMed Central Open Access full text articles), leading to creation of massive biomedical event databases, each of which containing millions of events. Sinece top-ranking event extraction systems are based on machine-learning approach and are trained on the narrow-domain, carefully selected Shared Task training data, their performance drops when being faced with the topically highly varied PubMed and PubMed Central documents. Specifically, false-positive predictions by these systems lead to generation of incorrect biomolecular events which are spotted by the end-users. This thesis proposes a novel post-processing approach, utilizing a combination of supervised and unsupervised learning techniques, that can automatically identify and filter out a considerable proportion of incorrect events from large-scale event databases, thus increasing the general credibility of those databases. The second part of this thesis is dedicated to a system we developed for hypothesis generation from large-scale event databases, which is able to discover novel biomolecular interactions among genes/gene-products. We cast the hypothesis generation problem as a supervised network topology prediction, i.e predicting new edges in the network, as well as types and directions for these edges, utilizing a set of features that can be extracted from large biomedical event networks. Routine machine learning evaluation results, as well as manual evaluation results suggest that the problem is indeed learnable. This work won the Best Paper Award in The 5th International Symposium on Languages in Biology and Medicine (LBM 2013).

Local and Regional Scale Determinants of Biodiversity Patterns in Boreal Agricultural Landscapes

This thesis examines the local and regional scale determinants of biodiversity patterns using existing species and environmental data. The research focuses on agricultural environments that have experienced rapid declines of biodiversity during past decades. Existing digital databases provide vast opportunities for habitat mapping, predictive mapping of species occurrences and richness and understanding the speciesenvironment relationships. The applicability of these databases depends on the required accuracy and quality of the data needed to answer the landscape ecological and biogeographical questions in hand. Patterns of biodiversity arise from confounded effects of different factors, such as climate, land cover and geographical location. Complementary statistical approaches that can show the relative effects of different factors are needed in biodiversity analyses in addition to classical multivariate models. Better understanding of the key factors underlying the variation in diversity requires the analyses of multiple taxonomic groups from different perspectives, such as richness, occurrence, threat status and population trends. The geographical coincidence of species richness of different taxonomic groups can be rather limited. This implies that multiple geographical regions should be taken into account in order to preserve various groups of species. Boreal agricultural biodiversity and in particular, distribution and richness of threatened species is strongly associated with various grasslands. Further, heterogeneous agricultural landscapes characterized by moderate field size, forest patches and non-crop agricultural habitats enhance the biodiversity of rural environments. From the landscape ecological perspective, the major threats to Finnish agricultural biodiversity are the decline of connected grassland habitat networks, and general homogenization of landscape structure resulting from both intensification and marginalization of agriculture. The maintenance of key habitats, such as meadows and pastures is an essential task in conservation of agricultural biodiversity. Furthermore, a larger landscape context should be incorporated in conservation planning and decision making processes in order to respond to the needs of different species and to maintain heterogeneous rural landscapes and viable agricultural diversity in the future.

Environments of Acitive Galaxies

This dissertation presents studies on the environments of active galaxies. Paper I is a case study of a cluster of galaxies containing BL Lac object RGB 1745+398. We measured the velocity dispersion, mass, and richness of the cluster. This was one of the most thorough studies of the environments of a BL Lac object. Methods used in the paper could be used in the future for studying other clusters as well. In Paper II we studied the environments of nearby quasars in the Sloan Digital Sky Survey (SDSS). We found that quasars have less neighboring galaxies than luminous inactive galaxies. In the large-scale structure, quasars are usually located at the edges of superclusters or even in void regions. We concluded that these low-redshift quasars may have become active only recently because the galaxies in low-density environments evolve later to the phase where quasar activity can be triggered. In Paper III we extended the analysis of Paper II to other types of AGN besides quasars. We found that different types of AGN have different large-scale environments. Radio galaxies are more concentrated in superclusters, while quasars and Seyfert galaxies prefer low-density environments. Different environments indicate that AGN have different roles in galaxy evolution. Our results suggest that activity of galaxies may depend on their environment on the large scale. Our results in Paper III raised questions of the cause of the environment-dependency in the evolution of galaxies. Because high-density large-scale environments contain richer groups and clusters than the underdense environments, our results could reflect smaller-scale effects. In Paper IV we addressed this problem by studying the group and supercluster scale environments of galaxies together. We compared the galaxy populations in groups of different richnesses in different large-scale environments. We found that the large-scale environment affects the galaxies independently of the group richness. Galaxies in low-density environments on the large scale are more likely to be star-forming than those in superclusters even if they are in groups with the same richness. Based on these studies, the conclusion of this dissertation is that the large-scale environment affects the evolution of galaxies. This may be caused by different “speed” of galaxy evolution in low and high-density environments: galaxies in dense environments reach certain phases of evolution earlier than galaxies in underdense environments. As a result, the low-density regions at low redshifts are populated by galaxies in earlier phases of evolution than galaxies in high-density regions.

Challenges in managing large-scale agile software development transformation

Adapting and scaling up agile concepts, which are characterized by iterative, self-directed, customer value focused methods, may not be a simple endeavor. This thesis concentrates on studying challenges in a large-scale agile software development transformation in order to enhance understanding and bring insight into the underlying factors for such emerging challenges. This topic is approached through understanding the concepts of agility and different methods compared to traditional plan-driven processes, complex adaptive theory and the impact of organizational culture on agile transformational efforts. The empirical part was conducted by a qualitative case study approach. The internationally operating software development case organization had a year of experience of an agile transformation effort during it had also undergone organizational realignment efforts. The primary data collection was conducted through semi-structured interviews supported by participatory observation. As a result the identified challenges were categorized under four broad themes: organizational, management, team dynamics and process related. The identified challenges indicate that agility is a multifaceted concept. Agile practices may bring visibility in issues of which many are embedded in the organizational culture or in the management style. Viewing software development as a complex adaptive system could facilitate understanding of the underpinning philosophy and eventually solving the issues: interactions are more important than processes and solving a complex problem, such a novel software development, requires constant feedback and adaptation to changing requirements. Furthermore, an agile implementation seems to be unique in nature, and agents engaged in the interaction are the pivotal part of the success of achieving agility. In case agility is not a strategic choice for whole organization, it seems additional issues may arise due to different ways of working in different parts of an organization. Lastly, detailed suggestions to mitigate the challenges of the case organization are provided.

Invenio v2.0: A Pythonic Framework for Large-Scale Digital Libraries

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Large Scale Repository Auditing to ISO 16363

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014