Webometric network analysis : mapping cooperation and geopolitical connections between local government administration on the web

Webben är en enorm källa för information. Innehållet på webbsidorna är en synlig typ av information, men webben innehåller även information av en annan typ, en mera gömd typ i form av sambanden och nätverken som hyperlänkarna skapar mellan webbsajterna och –sidorna som de kopplar ihop. Forskningsområdet webometri ämnar, bland annat, att skapa ny kunskap ur denna gömda information som finns inbyggt i hyperlänkarna samt att skapa förståelse för hurudana fenomen och förhållanden utanför webben kan finnas representerade i hyperlänkarna. Målet med denna forskning var att öka förståelse för användningen av hyperlänkar på webben och speciellt kommunernas användning av hyperlänkar. Denna forskning undersökte hur kommunerna i Egentliga Finland skapade och mottog hyperlänkar samt hurudana nätverk formades av dessa hyperlänkar. Forskningen kartlade nätverk av direkta länkar mellan kommunerna och av samlänkar till och från kommunerna och undersökte ifall dessa nätverk kunde användas för att undersöka geopolitiska förhållanden och samarbete mellan kommunerna i Egentliga Finland. De övergripande forskningsfrågorna som har besvarats i denna forskning är: 1) Från ett webometriskt perspektiv, hur använder kommunerna i Egentliga Finland webben? 2) Kan hyperlänkar (direkta länkar och samlänkar) användas för att kartlägga geopolitiska förhållanden och samarbete mellan kommuner? 3) Vilka är de viktigaste motiveringarna för att skapa länkar mellan, till och från kommunernas webbsajter? Denna forskning kom till ovanligt tydliga resultat för en webometrisk forskning, både när det gäller upptäckta geografiska faktorer som påverkar hyperlänkningarna och de klassificerade motivationerna för att skapa länkarna. Resultaten visade att de direkta hyperlänkarna mellan kommunerna kan användas för att kartlägga geopolitiska förhållanden och samarbete mellan kommunerna för att de direkta länkarna var motiverade av officiella orsaker och de var klart påverkade av distansen mellan kommunerna och av de ekonomiska regionerna. Samlänkningarna in till kommunerna visade sig fungera som ett mått för geografisk likhet mellan kommunerna, medan samlänkningarna ut från kommunerna visade potential för att kunna användas till för att kartlägga kommunernas gemensamma intressen. Forskningen kontribuerade även till utvecklandet av forskningsområdet webometri. En del av de viktigaste kontributionerna av denna forskning var utvecklandet av nya metoder för webometrisk forskning samt att öka kunskap om hur existerande metoder från nätverksanalys kan användas effektivt för webometrisk forskning. Resultaten från denna forskning och de utvecklade metoderna kan användas för snabba kartläggningar av diverse förhållanden mellan olika organisationer och företag genom att använda information gratis tillgängligt på webben.

Modeling and Analysis of Noise and Interconnects for On-Chip Communication Link Design

This thesis considers modeling and analysis of noise and interconnects in onchip communication. Besides transistor count and speed, the capabilities of a modern design are often limited by on-chip communication links. These links typically consist of multiple interconnects that run parallel to each other for long distances between functional or memory blocks. Due to the scaling of technology, the interconnects have considerable electrical parasitics that affect their performance, power dissipation and signal integrity. Furthermore, because of electromagnetic coupling, the interconnects in the link need to be considered as an interacting group instead of as isolated signal paths. There is a need for accurate and computationally effective models in the early stages of the chip design process to assess or optimize issues affecting these interconnects. For this purpose, a set of analytical models is developed for on-chip data links in this thesis. First, a model is proposed for modeling crosstalk and intersymbol interference. The model takes into account the effects of inductance, initial states and bit sequences. Intersymbol interference is shown to affect crosstalk voltage and propagation delay depending on bus throughput and the amount of inductance. Next, a model is proposed for the switching current of a coupled bus. The model is combined with an existing model to evaluate power supply noise. The model is then applied to reduce both functional crosstalk and power supply noise caused by a bus as a trade-off with time. The proposed reduction method is shown to be effective in reducing long-range crosstalk noise. The effects of process variation on encoded signaling are then modeled. In encoded signaling, the input signals to a bus are encoded using additional signaling circuitry. The proposed model includes variation in both the signaling circuitry and in the wires to calculate the total delay variation of a bus. The model is applied to study level-encoded dual-rail and 1-of-4 signaling. In addition to regular voltage-mode and encoded voltage-mode signaling, current-mode signaling is a promising technique for global communication. A model for energy dissipation in RLC current-mode signaling is proposed in the thesis. The energy is derived separately for the driver, wire and receiver termination.

Towards combining interactive mobile TV and smart spaces : architectures, tools and application development

Technological developments in microprocessors and ICT landscape have made a shift to a new era where computing power is embedded in numerous small distributed objects and devices in our everyday lives. These small computing devices are ne-tuned to perform a particular task and are increasingly reaching our society at every level. For example, home appliances such as programmable washing machines, microwave ovens etc., employ several sensors to improve performance and convenience. Similarly, cars have on-board computers that use information from many di erent sensors to control things such as fuel injectors, spark plug etc., to perform their tasks e ciently. These individual devices make life easy by helping in taking decisions and removing the burden from their users. All these objects and devices obtain some piece of information about the physical environment. Each of these devices is an island with no proper connectivity and information sharing between each other. Sharing of information between these heterogeneous devices could enable a whole new universe of innovative and intelligent applications. The information sharing between the devices is a diffcult task due to the heterogeneity and interoperability of devices. Smart Space vision is to overcome these issues of heterogeneity and interoperability so that the devices can understand each other and utilize services of each other by information sharing. This enables innovative local mashup applications based on shared data between heterogeneous devices. Smart homes are one such example of Smart Spaces which facilitate to bring the health care system to the patient, by intelligent interconnection of resources and their collective behavior, as opposed to bringing the patient into the health system. In addition, the use of mobile handheld devices has risen at a tremendous rate during the last few years and they have become an essential part of everyday life. Mobile phones o er a wide range of different services to their users including text and multimedia messages, Internet, audio, video, email applications and most recently TV services. The interactive TV provides a variety of applications for the viewers. The combination of interactive TV and the Smart Spaces could give innovative applications that are personalized, context-aware, ubiquitous and intelligent by enabling heterogeneous systems to collaborate each other by sharing information between them. There are many challenges in designing the frameworks and application development tools for rapid and easy development of these applications. The research work presented in this thesis addresses these issues. The original publications presented in the second part of this thesis propose architectures and methodologies for interactive and context-aware applications, and tools for the development of these applications. We demonstrated the suitability of our ontology-driven application development tools and rule basedapproach for the development of dynamic, context-aware ubiquitous iTV applications.

Identification and application of bile metabolites to assess the exposure of fish to pharmaceuticals in the environment

Thousands of tons of pharmaceuticals are consumed yearly worldwide. Due to the continuous and increasing consumption and their incomplete elimination in wastewater treatment plants (WWTP), pharmaceuticals and their metabolites can be detected in receiving waters, although at low concentrations (ng to low μg/L). As bioactive molecules the presence of pharmaceuticals in the aquatic environment must be considered potentially hazardous for the aquatic organisms. In this thesis, the biotransformation and excretion of pharmaceuticals in fish was studied. The main biotransformation pathways of three anti‐inflammatory drugs, diclofenac, naproxen and ibuprofen, in rainbow trout were glucuronidation and taurine conjugation of the parent compounds and their phase I metabolites. The same metabolites were present in fish bile in aquatic exposures as in fish dosed with intraperitoneal injection. Higher bioconcentration factor in bile (BCFbile) was found for ibuprofen when compared to diclofenac and naproxen. Laboratory exposure studies were followed by a study of uptake of pharmaceuticals in a wild fish population living in lake contaminated with WWTP effluents. Of the analyzed 17 pharmaceuticals and six phase I metabolites, only diclofenac, naproxen and ibuprofen was present in bream and roach bile. It was shown, that diclofenac, naproxen and ibuprofen excreted by the liver can be found in rainbow trout and in two native fish species living in the receiving waters. In the bream and roach bile, the concentrations of diclofenac, naproxen and ibuprofen were roughly 1000 times higher than those found in the lake water, while in the laboratory exposures, the bioconcentration of the compounds and their metabolites in rainbow trout bile were at the same level as in wild fish or an order of magnitude higher. Thus, the parent compounds and their metabolites in fish bile can be used as a reliable biomarker to monitor the exposure of fish to environmental pharmaceuticals present in water receiving discharges from WWTPs.

Digital Preservation Tools, Practices, and Policies in Islandora

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

Phylogenetic Analysis of Avidins and Expression of Novel Avidins from Lactrodectus hesperus and Hoeflea phototrophica

Avidins (Avds) are homotetrameric or homodimeric glycoproteins with typically less than 130 amino acid residues per monomer. They form a highly stable, non-covalent complex with biotin (vitamin H) with Kd = 10-15 M (for chicken Avd). The best-studied Avds are the chicken Avd from Gallus gallus and streptavidin from Streptomyces avidinii, although other Avd studies have also included Avds from various origins, e.g., from frogs, fishes, mushrooms and from many different bacteria. Several engineered Avds have been reported as well, e.g., dual-chain Avds (dcAvds) and single-chain Avds (scAvds), circular permutants with up to four simultaneously modifiable ligand-binding sites. These engineered Avds along with the many native Avds have potential to be used in various nanobiotechnological applications. In this study, we made a structure-based alignment representing all currently available sequences of Avds and studied the evolutionary relationship of Avds using phylogenetic analysis. First, we created an initial multiple sequence alignment of Avds using 42 closely related sequences, guided by the known Avd crystal structures. Next, we searched for non-redundant Avd sequences from various online databases, including National Centre for Biotechnology Information and the Universal Protein Resource; the identified sequences were added to the initial alignment to expand it to a final alignment of 242 Avd sequences. The MEGA software package was used to create distance matrices and a phylogenetic tree. Bootstrap reproducibility of the tree was poor at multiple nodes and may reflect on several possible issues with the data: the sequence length compared is relatively short and, whereas some positions are highly conserved and functional, others can vary without impinging on the structure or the function, so there are few informative sites; it may be that periods of rapid duplication have led to paralogs and that the differences among them are within the error limit of the data; and there may be other yet unknown reasons. Principle component analysis applied to alternative distance data did segregate the major groups, and success is likely due to the multivariate consideration of all the information. Furthermore, based on our extensive alignment and phylogenetic analysis, we expressed two novel Avds, lacavidin from Lactrodectus Hesperus, a western black widow spider, and hoefavidin from Hoeflea phototrophica, an aerobic marine bacterium, the ultimate aim being to determine their X-ray structures. These Avds were selected because of their unique sequences: lacavidin has an N-terminal Avd-like domain but a long C-terminal overhang, whereas hoefavidin was thought to be a dimeric Avd. Both these Avds could be used as novel scaffolds in biotechnological applications.

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.

A performance analysis of conventional and fundamental exchange traded funds: ETFs and their risk-return characteristics in relation to building institutional investor’s passive portfolio

An exchange traded fund (ETF) is a financial instrument that tracks some predetermined index. Since their initial establishment in 1993, ETFs have grown in importance in the field of passive investing. The main reason for the growth of the ETF industry is that ETFs combine benefits of stock investing and mutual fund investing. Although ETFs resemble mutual funds in many ways, also many differences occur. In addition, ETFs not only differ from mutual funds but also differ among each other. ETFs can be divided into two categories, i.e. market capitalisation ETFs and fundamental (or strategic) ETFs, and further into subcategories depending on their fundament basis. ETFs are a useful tool for diversification especially for a long-term investor. Although the economic importance of ETFs has risen drastically during the past 25 years, the differences and risk-return characteristics of fundamental ETFs have yet been rather unstudied area. In effect, no previous research on market capitalisation and fundamental ETFs was found during the research process. For its part, this thesis seeks to fill this research gap. The studied data consist of 50 market capitalisation ETFs and 50 fundamental ETFs. The fundaments, on which the indices that the fundamental ETFs track, were not limited nor segregated into subsections. The two types of ETFs were studied at an aggregate level as two different research groups. The dataset ranges from June 2006 to December 2014 with 103 monthly observations. The data was gathered using Bloomberg Terminal. The analysis was conducted as an econometric performance analysis. In addition to other econometric measures, the methods that were used in the performance analysis included modified Value-at-Risk, modified Sharpe ratio and Treynor ratio. The results supported the hypothesis that passive market capitalisation ETFs outperform active fundamental ETFs in terms of risk-adjusted returns, though the difference is rather small. Nevertheless, when taking into account the higher overall trading costs of the fundamental ETFs, the underperformance gap widens. According to the research results, market capitalisation ETFs are a recommendable diversification instrument for a long-term investor. In addition to better risk-adjusted returns, passive ETFs are more transparent and the bases of their underlying indices are simpler than those of fundamental ETFs. ETFs are still a young financial innovation and hence data is scarcely available. On future research, it would be valuable to research the differences in risk-adjusted returns also between the subsections of fundamental ETFs.

Intellectual capital, knowledge management practices and firm performance

Researchers have widely recognised and accepted that firm performance is increasingly related to knowledge-based issues. Two separately developed literature streams, intellectual capital (IC) and knowledge management (KM), have been established as the key discussions related to knowledge-based competitive advantage of the firm. Intellectual capital has provided evidence on the strategic key intangible resources of the firm, which could be deployed to create competitive advantage. Knowledge management, in turn, has focused on the managerial processes and practices which can be used to leverage IC to create competitive advantage. Despite extensive literature on both issues, some notable research gaps remain to be closed. In effect, one major gap within the knowledge management research is the lack of understanding related to its influence on firm performance, while IC researchers have articulated a need to utilise more finegrained conceptual models to better understand the key strategic value-creating resources of the firm. In this dissertation, IC is regarded as the entire intellectual capacity, knowledge and competences of the firm that can be leveraged to achieve sustained competitive advantage. KM practices are defined as organisational and managerial activities that enable the firm to leverage its IC to create value. The objective of this dissertation is to answer the research question: “What is the relationship between intellectual capital, knowledge management practices and firm performance?” Five publications have addressed the research question using different approaches. The first two publications were systematic literature reviews of the extant empirical IC and KM research, which established the current state of understanding regarding the relationship between IC, KM practices and firm performance. Publications III and IV were empirical research articles that assessed the developed conceptual model related to IC, KM practices and firm performance. Finally, Publication V was among the first research papers to merge IC and KM disciplines in order to find out which configurations could yield organisational benefits in terms of innovation and market performance outcomes.