Secure Bluetooth Audio Transmission System

The growing spread of small but powerful mobile devices (such as PDAs, mobile phone, Internet Tablet, etc.) opens up new scenarios in which users can interact with such devices in many environments in order to access the information at different locations. In this thesis, a ubiquitous computing based system called Secure Bluetooth Audio Transmission System is introduced. This system is situated in a large public place (like airport, festival venues, etc.), where voice messages are conveyed from the system to users' Bluetooth headsets in order to inform users the latest flight schedule and other public information. The reliability of the message is secured by adopting an authorization strategy and ECDSA. In order to assess and evaluate the risks and potential weaknesses of the system, an easy-to-use prototype implementation was written and tested. Other possible uses and further research were also considered.

Energy-efficient control strategies for variable speed driven parallel pumping systems based on pump operation point monitoring with frequency converters

The pumping processes requiring wide range of flow are often equipped with parallelconnected centrifugal pumps. In parallel pumping systems, the use of variable speed control allows that the required output for the process can be delivered with a varying number of operated pump units and selected rotational speed references. However, the optimization of the parallel-connected rotational speed controlled pump units often requires adaptive modelling of both parallel pump characteristics and the surrounding system in varying operation conditions. The available information required for the system modelling in typical parallel pumping applications such as waste water treatment and various cooling and water delivery pumping tasks can be limited, and the lack of real-time operation point monitoring often sets limits for accurate energy efficiency optimization. Hence, alternatives for easily implementable control strategies which can be adopted with minimum system data are necessary. This doctoral thesis concentrates on the methods that allow the energy efficient use of variable speed controlled parallel pumps in system scenarios in which the parallel pump units consist of a centrifugal pump, an electric motor, and a frequency converter. Firstly, the suitable operation conditions for variable speed controlled parallel pumps are studied. Secondly, methods for determining the output of each parallel pump unit using characteristic curve-based operation point estimation with frequency converter are discussed. Thirdly, the implementation of the control strategy based on real-time pump operation point estimation and sub-optimization of each parallel pump unit is studied. The findings of the thesis support the idea that the energy efficiency of the pumping can be increased without the installation of new, more efficient components in the systems by simply adopting suitable control strategies. An easily implementable and adaptive control strategy for variable speed controlled parallel pumping systems can be created by utilizing the pump operation point estimation available in modern frequency converters. Hence, additional real-time flow metering, start-up measurements, and detailed system model are unnecessary, and the pumping task can be fulfilled by determining a speed reference for each parallel-pump unit which suggests the energy efficient operation of the pumping system.

Calculation analysis of energy saving tools for fan and pump applications

This thesis analyses the calculation of FanSave and PumpSave energy saving tools calculation. With these programs energy consumption of variable speed drive control for fans and pumps can be compared to other control methods. With FanSave centrifugal and axial fans can be examined and PumpSave deals with centrifugal pumps. By means of these programs also suitable frequency converter can be chosen from the ABB collection. Programs need as initial values information about the appliances like amount of flow and efficiencies. Operation time is important factor when calculating the annual energy consumption and information about it are the length and profile. Basic theory related to fans and pumps is introduced without more precise instructions for dimensioning. FanSave and PumpSave contain various methods for flow control. These control methods are introduced in the thesis based on their operational principles and suitability. Also squirrel cage motor and frequency converter are introduced because of their close involvement to fans and pumps. Second part of the thesis contains comparison between results of FanSave’s and PumpSave’s calculation and performance curve based calculation. Also laboratory tests were made with centrifugal and axial fan and also with centrifugal pump. With the results from this thesis the calculation of these programs can be adjusted to be more accurate and also some new features can be added.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

Quasiclassical Approach to the Vortex State in Iron-based Superconductors

The quasiclassical approach was applied to the investigation of the vortex properties in the ironbased superconductors. The special attention was paid to manifestation of the nonlocal effects of the vortex core structure. The main results are as follows: (i) The effects of the pairing symmetries (s+ and s₊₊) on the cutoff parameter of field distribution, ξh, in stoichiometric (like LiFeAs) and nonstoichiometric (like doped BaFe₂As₂) iron pnictides have been investigated using Eilenberger quasiclassical equations. Magnetic field, temperature and impurity scattering dependences of ξh have been calculated. Two opposite behavior have been discovered. The ξh /ξc2 ratio is less in s+ symmetry when intraband impurity scattering (Γ₀) is much larger than one and much larger than interband impurity scattering (Γπ), i.e. in nonstoichiometric iron pnictides. Opposite, the value ξh /ξc2 is higher in s+ case and the field dependent curve is shifted upward from the "clean" case (Γ₀ = Γπ = 0) for stoichiometric iron pnictides (Γ₀ = Γπ ≪ 1). (ii) Eilenberger approach to the cutoff parameter, ξh, of the field distribution in the mixed state of high

Capacity of an I-beam made of S960 QC based on Eurocode 3

The capacity of beams is a very important factor in the study of durability of structures and structural members. The capacity of a high-strength steel I-beam made of S960 QC was investigated in this study. The investigation included assessment of the service limits and ultimate limits of the steel beam. The thesis was done according to European standards for steel structures, Eurocode 3. An analytical method was used to determine the throat thickness, deformation, elastic and plastic moment capacities as well as the fatigue life of the beam. The results of the analytical method were compared with those obtained by Finite Element Analysis (FEA). Elastic moment capacity obtained by the analytical method was 172 kNm. FEA and the analytical method predicted the maximum lateral-torsional buckling (LTB) capacity in the range of 90-93 kNm and the probability of failure as a result of LTB is estimated to be 50%. The lateral buckling capacity meant that the I-beam can carry a safe load of 300 kN instead of the initial load of 600 kN. The beam is liable to fail shortly after exceeding the elastic moment capacity. Based on results in of the different approaches, it was noted that FEA predicted higher deformation values on the load-deformation curve than the analytical results. However, both FEA and the analytical methods predicted identical results for nominal stress range and moment capacities. Fatigue life was estimated to be in the range of 53000-64000 cycles for bending stress range using crack propagation equation and strength-life approach. As Eurocode 3 is limited to steel grades up to S690, results for S960 must be verified with experimental data and appropriate design rules.