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Nimeke- ja tekijätiedot nimiönkehyksissä

On Distributed Storage Codes

Distributed storage systems are studied. The interest in such system has become relatively wide due to the increasing amount of information needed to be stored in data centers or different kinds of cloud systems. There are many kinds of solutions for storing the information into distributed devices regarding the needs of the system designer. This thesis studies the questions of designing such storage systems and also fundamental limits of such systems. Namely, the subjects of interest of this thesis include heterogeneous distributed storage systems, distributed storage systems with the exact repair property, and locally repairable codes. For distributed storage systems with either functional or exact repair, capacity results are proved. In the case of locally repairable codes, the minimum distance is studied. Constructions for exact-repairing codes between minimum bandwidth regeneration (MBR) and minimum storage regeneration (MSR) points are given. These codes exceed the time-sharing line of the extremal points in many cases. Other properties of exact-regenerating codes are also studied. For the heterogeneous setup, the main result is that the capacity of such systems is always smaller than or equal to the capacity of a homogeneous system with symmetric repair with average node size and average repair bandwidth. A randomized construction for a locally repairable code with good minimum distance is given. It is shown that a random linear code of certain natural type has a good minimum distance with high probability. Other properties of locally repairable codes are also studied.

Nanoparticle-Assisted Immunoassays for Point-of-Care Testing - With Specific Interest in Minimally Interference-Prone Assays for Cardiac Troponin I

Cardiac troponins (cTn) I and T are the current golden standard biochemical markers in the diagnosis and risk stratification of patients with suspected acute coronary syndrome. During the past few years, novel assays capable of detecting cTn‐concentrations in >50% of apparently healthy individuals have become readily available. With the emerging of these high sensitivity cTn assays, reductions in the assay specificity have caused elevations in the measured cTn levels that do not correlate with the clinical picture of the patient. The increased assay sensitivity may reveal that various analytical interference mechanisms exist. This doctoral thesis focused on developing nanoparticle‐assisted immunometric assays that could possibly be applied to an automated point‐of‐care system. The main objective was to develop minimally interference‐prone assays for cTnI by employing recombinant antibody fragments. Fast 5‐ and 15‐minute assays for cTnI and D‐dimer, a degradation product of fibrin, based on intrinsically fluorescent nanoparticles were introduced, thus highlighting the versatility of nanoparticles as universally applicable labels. The utilization of antibody fragments in different versions of the developed cTnI‐assay enabled decreases in the used antibody amounts without sacrificing assay sensitivity. In addition, the utilization of recombinant antibody fragments was shown to significantly decrease the measured cTnI concentrations in an apparently healthy population, as well as in samples containing known amounts of potentially interfering factors: triglycerides, bilirubin, rheumatoid factors, or human anti‐mouse antibodies. When determining the specificity of four commercially available antibodies for cTnI, two out of the four cross‐reacted with skeletal troponin I, but caused crossreactivity issues in patient samples only when paired together. In conclusion, the results of this thesis emphasize the importance of careful antibody selection when developing cTnI assays. The results with different recombinant antibody fragments suggest that the utilization of antibody fragments should strongly be encouraged in the immunoassay field, especially with analytes such as cTnI that require highly sensitive assay approaches.

Spatial modeling techniques for mapping and characterization of acid sulfate soils

Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.

The Impact of the 2007-2009 Financial Crisis on the Relationship between Central Bank Rates and the Corresponding Interbank Interest Rates in 2002-2014

The role of central banks throughout the global financial system has become even more important during and after the events of the financial crisis. In order to stabilize the market conditions and provide solid ground for future development, the central banks use discount rate as their primary monetary policy tool in many developed and emerging economies. The purpose of this thesis is to examine how the relationship between central bank rates and corresponding interbank rates has developed before, during and after the crisis period of 2007-2009 in five developed countries and five emerging market countries. The results indicate that during the before-crisis period the interest rate markets reacted diversely but the joint recovery attempts of global economies seem to have stabilized the reactions during and especially after the crisis. The crisis also seems to have highlighted the characteristics of each country’s survival strategy as the role of other policy instruments arose.

Use of airborne laser scanner data in demanding forest conditions

Most of the applications of airborne laser scanner data to forestry require that the point cloud be normalized, i.e., each point represents height from the ground instead of elevation. To normalize the point cloud, a digital terrain model (DTM), which is derived from the ground returns in the point cloud, is employed. Unfortunately, extracting accurate DTMs from airborne laser scanner data is a challenging task, especially in tropical forests where the canopy is normally very thick (partially closed), leading to a situation in which only a limited number of laser pulses reach the ground. Therefore, robust algorithms for extracting accurate DTMs in low-ground-point-densitysituations are needed in order to realize the full potential of airborne laser scanner data to forestry. The objective of this thesis is to develop algorithms for processing airborne laser scanner data in order to: (1) extract DTMs in demanding forest conditions (complex terrain and low number of ground points) for applications in forestry; (2) estimate canopy base height (CBH) for forest fire behavior modeling; and (3) assess the robustness of LiDAR-based high-resolution biomass estimation models against different field plot designs. Here, the aim is to find out if field plot data gathered by professional foresters can be combined with field plot data gathered by professionally trained community foresters and used in LiDAR-based high-resolution biomass estimation modeling without affecting prediction performance. The question of interest in this case is whether or not the local forest communities can achieve the level technical proficiency required for accurate forest monitoring. The algorithms for extracting DTMs from LiDAR point clouds presented in this thesis address the challenges of extracting DTMs in low-ground-point situations and in complex terrain while the algorithm for CBH estimation addresses the challenge of variations in the distribution of points in the LiDAR point cloud caused by things like variations in tree species and season of data acquisition. These algorithms are adaptive (with respect to point cloud characteristics) and exhibit a high degree of tolerance to variations in the density and distribution of points in the LiDAR point cloud. Results of comparison with existing DTM extraction algorithms showed that DTM extraction algorithms proposed in this thesis performed better with respect to accuracy of estimating tree heights from airborne laser scanner data. On the other hand, the proposed DTM extraction algorithms, being mostly based on trend surface interpolation, can not retain small artifacts in the terrain (e.g., bumps, small hills and depressions). Therefore, the DTMs generated by these algorithms are only suitable for forestry applications where the primary objective is to estimate tree heights from normalized airborne laser scanner data. On the other hand, the algorithm for estimating CBH proposed in this thesis is based on the idea of moving voxel in which gaps (openings in the canopy) which act as fuel breaks are located and their height is estimated. Test results showed a slight improvement in CBH estimation accuracy over existing CBH estimation methods which are based on height percentiles in the airborne laser scanner data. However, being based on the idea of moving voxel, this algorithm has one main advantage over existing CBH estimation methods in the context of forest fire modeling: it has great potential in providing information about vertical fuel continuity. This information can be used to create vertical fuel continuity maps which can provide more realistic information on the risk of crown fires compared to CBH.

Stories from the City, Stories from the Sea - How place brands are perceived differently from the points of view of a local and a tourist

Tämä tutkielma käsittelee paikkamarkkinointia ja paikkabrändäystä. Tutkielmassa tarkastellaan paikallisen ja turistin tapoja muodostaa kaupunkibrändi; mistä palasista brändi muodostuu kirjallisuuden ja haastateltavien mukaan, koetaanko eri palaset vaihtelevissa määrin tärkeiksi riippuen siitä, tarkastellaanko paikkaa paikallisena vai turistina, ja löytyykö jotain yhteisiä retorisia nimittäjiä sille, miten kotikaupungista puhutaan verrattuna lomakaupunkiin. Tutkimuksessa haastateltiin yli kolmeakymmentä henkilöä heidän kotikaupungeistaan ja kaupungeista, joihin he olivat matkustaneet lomalle. Haastateltavat olivat suurinpiirtein samanikäisiä, mutta eri kaupungeista ja matkustaneet eri paikkoihin. Haastateltavia pyydettiin ensin kuvailemaan vapaasti kotikaupunkiaan ja sen jälkeen kaupungista kysyttiin kirjallisuuteen perustuen kysymyksiä. Sama menetelmä toistettiin lomakohteen suhteen. Tutkimuksesta selvisi, että paikkabrändi muodostetaan samoista komponenteista, mutta joidenkin komponenttien merkitys on tärkeämpi kotikaupungissa, kun taas toiset komponentit ovat tärkeitä lomakohteen suhteen. Ihmiset ja kulttuuri yleisesti koettiin tärkeinä komponentteina molemmista paikkabrändeistä puhuttaessa, kun taas kotikaupungin brändinmuodostukseen kuului vahvemmin lait ja muut käytännölliset menettelytavat kuten liikenteen toimivuus. Lomakohteen brändinmuodostuksessa vapaudella tehdä mitä haluaa oli suuri merkitys ja vapautta nähtiin eri muodoissa. Retoriikka kotikaupungista puhuttaessa oli selvästi negatiivista, kun taas lomakohteesta puhuttiin yleisesti ottaen positiiviseen sävyyn. Suhde kotikaupunkiin oli ambivalentti, sillä huonojakin puolia mainittaessa niitä puolusteltiin, tai kotikaupungista mainittiin loppujen lopuksi jotain hyvää. Tutkimusten tuloksiin perustuen toimenpidesuosituksina ehdotetaan olemassaolevan autenttisen kulttuurin ylläpitämäistä, korostamista ja kaupungin orgaanista kehittämistä suuntaan, jossa se on hyvä paikka niin elämiseen kuin lomailuun. Identiteetti, imago ja ihmiset kietoutuvat tiiviisti yhteen, minkä vuoksi kaupunkisuunnittelun- ja kehittämisen tehtävänä on pitää huolta, että kaupunki on onnistunut molempien ryhmien suhteen, ja molemmat ryhmät levittävät kaupungista positiivista sanomaa.