Tuottavuuden ja investointitehokkuuden parantaminen kunnallisteknisissä töissä

Tutkimuksen tavoitteena oli selvittää keinoja parantaa tuottavuutta ja investointitehokkuutta kunnallisteknisissä töissä. Tutkimusmenetelmäksi valittiin konstruktiivinen tutkimusmenetelmä, jossa käytännölliseen ongelmaan luodaan teoriapohjan kautta ratkaisuehdotus. Työn teoriaosuus käsittelee palveluiden tuottavuutta ja sen mittaamista. Työn tuloksena syntyi excel-työkalu, jonka avulla on mahdollista tarkastella palveluntuottajan konekannan aiheuttamia kustannuksia ja tuottoja. Työkalu laskee konekohtaiset kustannukset ja tuotot, joiden avulla palveluntuottajalle on mahdollista osoittaa aiempien investointien kannattavuus. Työkalu laskee kustannus- ja tuottoarvion myös vaihtoehtoiselle konekannalle, jossa alhaisen käyttöasteen koneita korvataan monipuolisemmalla kalustolla. Palveluntuottajan konekannan hallinta ja kustannusrakenteen tarkka määrittely ovat tärkeässä roolissa tuottavuuden ja kannattavuuden kehittämisessä. Työkalu mahdollistaa myös eri kustannuserissä tapahtuvien muutosten vaikutusten arvioinnin, mikä auttaa palveluntuottajia toiminnan pitkäjänteisessä kehittämisessä.

Virtuaaliprototyypin käyttö roottorin dynamiikan analysoinnissa

Työn tavoitteena oli selvittää kaupallisen dynamiikansimulointiohjelmiston so-veltuvuus roottoridynamiikan analysointiin. Työssä keskityttiin erityisesti rootto-rin dynamiikkaan vaikuttavien epäideaalisuuksien mallintamiseen. Simulointitu-losten tarkkuutta selvitettiin mittauksilla. Lisäksi vertailtiin yleiskäyttöisen dyna-miikan simulointiohjelmiston ja roottoridynamiikan erikoisohjelmiston teoriaa. Tutkittava roottori oli paperikoneen putkitela. Telan joustavuus kuvattiin ele-menttimenetelmällä ratkaistujen moodien avulla. Elementtimallissa huomioitiin telan vaipan seinämänpaksuusvaihtelu, joka vaikuttaa telan massa- ja jäykkyysja-kaumaan. Dynamiikkaohjelmistossa mallinnettiin telan tuennasta tulevat herätteet. Dynamiikkaohjelmistona käytettiin ADAMS:ia ja FEM-ohjelmana ANSYS:stä. Tuloksista havaittiin käytetyn menetelmän soveltuvan roottoridynamiikan ana-lysointiin ja roottorin epäideaalisuuksien mallintamiseen. Simulointimallilla saa-tiin esille murtolukukriittiset pyörimisnopeudet ja telan kriittinen pyörimisnopeus vastasi hyvin mittaustuloksia.

Extreme Observables and Optimal Measurements in Quantum Theory

Optimization of quantum measurement processes has a pivotal role in carrying out better, more accurate or less disrupting, measurements and experiments on a quantum system. Especially, convex optimization, i.e., identifying the extreme points of the convex sets and subsets of quantum measuring devices plays an important part in quantum optimization since the typical figures of merit for measuring processes are affine functionals. In this thesis, we discuss results determining the extreme quantum devices and their relevance, e.g., in quantum-compatibility-related questions. Especially, we see that a compatible device pair where one device is extreme can be joined into a single apparatus essentially in a unique way. Moreover, we show that the question whether a pair of quantum observables can be measured jointly can often be formulated in a weaker form when some of the observables involved are extreme. Another major line of research treated in this thesis deals with convex analysis of special restricted quantum device sets, covariance structures or, in particular, generalized imprimitivity systems. Some results on the structure ofcovariant observables and instruments are listed as well as results identifying the extreme points of covariance structures in quantum theory. As a special case study, not published anywhere before, we study the structure of Euclidean-covariant localization observables for spin-0-particles. We also discuss the general form of Weyl-covariant phase-space instruments. Finally, certain optimality measures originating from convex geometry are introduced for quantum devices, namely, boundariness measuring how ‘close’ to the algebraic boundary of the device set a quantum apparatus is and the robustness of incompatibility quantifying the level of incompatibility for a quantum device pair by measuring the highest amount of noise the pair tolerates without becoming compatible. Boundariness is further associated to minimum-error discrimination of quantum devices, and robustness of incompatibility is shown to behave monotonically under certain compatibility-non-decreasing operations. Moreover, the value of robustness of incompatibility is given for a few special device pairs.

Explaining the intention to play and behavior of playing sports betting games of young Finnish adults : an application of the theory of planned behavior

The aim of this Master’s Thesis was to examine the determinants of intention and behavior of playing sports betting games in order to explain the intention to play in a more precise way and to be able to understand the behavior of playing. The theory of planned behavior was applied in explaining the intention of young Finnish adults aged 18 to 34. A quantitative research method was applied and an online survey was sent to the students of Lappeenranta University of Technology and to the subscribers of Urheilulehti in order to reach a sample that present the young population of Finland. The theory of the study focused on the theory of planned behavior and its antecedents, attitude towards behavior, subjective norms, perceived behavioral control as well as motivation. By analyzing the data, causal relationships were found through which the explanation of intention was possible. The results showed that attitude towards playing, subjective norms, perceived behavioral control and motivation impact the formation of intention significantly. The results also indicated that intention impacts significantly to the playing frequency.

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.

Heat-transfer improvements in an axial-flux permanent-magnet synchronous machine

Axial-flux machines tend to have cooling difficulties since it is difficult to arrange continuous heat path between the stator stack and the frame. One important reason for this is that no shrink fitting of the stator is possible in an axial-flux machine. Using of liquid-cooled end shields does not alone solve this issue. Cooling of the rotor and the end windings may also be difficult at least in case of two-stator-single-rotor construction where air circulation in the rotor and in the end-winding areas may be difficult to arrange. If the rotor has significant losses air circulation via the rotor and behind the stator yokes should be arranged which, again, weakens the stator cooling. In this paper we study a novel way of using copper bars as extra heat transfer paths between the stator teeth and liquid cooling pools in the end shields. After this the end windings still suffer of low thermal conductivity and means for improving this by high-heat-conductance material was also studied. The design principle of each cooling system is presented in details. Thermal models based on Computational Fluid Dynamics (CFD) are used to analyse the temperature distribution in the machine. Measurement results are provided from different versions of the machine. The results show that significant improvements in the cooling can be gained by these steps.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

Alternative banking: theory and evidence from Europe

Since financial liberalization in the 1980s, non-profit maximizing, stakeholder-oriented banks have outperformed private banks in Europe. This article draws on empirical research, banking theory and theories of the firm to explain this apparent anomaly for neo-liberal policy and contemporary market-based banking theory. The realization of competitive advantages by alternative banks (savings banks, cooperative banks and development banks) has significant implications for conceptions of bank change, regulation and political economy.

Global instability of currencies: reasons and perspectives according to the state-corporation hegemonic stability theory

This paper analyses reasons of the instability of the world monetary system. The author considers this problem from historical and contemporary perspectives. According to presented point of view banknotes and electronic money which replaced gold and silver coins in popular circulation are the most important reason of the instability. There are also proven positive and negative consequences of money instability. Reforms of the world monetary system need agreement within the global collective hegemony of state-powers and transnational corporations.

Neoliberalism and global capital mobility: a necessary reconsideration of textbook trade theory

Textbook theory ignores capital flows: trade determines exchange rates and specialisation. Approaches taking the effects of capital movements adequately into account are needed, and a new theory of economic policy including measures to protect the real economy from external volatility. Equilibrating textbook mechanisms cannot work unless trade-caused surpluses and deficits set exchange rates. To allow orthodox trade theory to work one must hinder capital flows from destroying its very basis, which the IMF and wrong regulatory decisions have done, penalising production and trade. A new, real economy based theory is proposed, a Neoclassical agenda of controlling capital flows and speculation.