Optimization of a dynamic district heating power plant

The purpose of this Thesis is to find the most optimal heat recovery solution for Wärtsilä’s dynamic district heating power plant considering Germany energy markets as in Germany government pays subsidies for CHP plants in order to increase its share of domestic power production to 25 % by 2020. Different heat recovery connections have been simulated dozens to be able to determine the most efficient heat recovery connections. The purpose is also to study feasibility of different heat recovery connections in the dynamic district heating power plant in the Germany markets thus taking into consideration the day ahead electricity prices, district heating network temperatures and CHP subsidies accordingly. The auxiliary cooling, dynamical operation and cost efficiency of the power plant is also investigated.

Magnetization studies of polystyrene/multiwall carbon nanotube composite films

Lappeenranta University of Technology School of Technology Technical Physics Evgenii Zhukov MAGNETIZATION STUDIES OF POLYSTYRENE/MULTIWALL CARBON NANOTUBE COMPOSITE FILMS Master’s thesis 2015 55 pages, 41 pictures, 9 Tables. Examiners: Professor Erkki Lähderanta D.Sc. Ivan Zakharchuk Keywords: polystyrene, multi-walled carbon nanotubes, MWCNT, composite, magnetization, SQUID. In this thesis magnetic properties of polystyrene/multiwall carbon nanotube (MWCNT) composites are investigated with Quantum Design SQUID magnetometer (MPMS XL). The surface of the composite films is studied via BRUKER Multimode 8 Atomic Force Microscope, as well. The polystyrene/MWCNT composites have been prepared by the group of professor Okotrub (Physics Chemistry of Nanomaterials laboratory, Nikolaev Institute of Inorganic Chemistry, Russia). The composite films have been prepared by solution processing and stretching method. The approximate length and inner diameter of the MWCNTs used in fabrication are 260 μm and 10 nm, respectively. The content of MWCNTs is 1 and 2.5 contents percent (wt%) for studied samples. The stretching of the samples is 30% for samples with 1 and 2.5 wt% content, and one sample with 1 wt% loading of MWCNTs is 100% stretched. MWCNTs aligned perpendicular to a silicon substrate are used as a reference sample. The magnetization field dependencies of the samples exhibit hysteresis behavior. The values of saturation magnetization of composite films are much less compared to that of the reference sample. The saturation magnetization coercitivity field value drops with decrease of MWCNT content. At high magnetic fields strong presence of diamagnetism is observed. Measurements in magnetic field parallel and perpendicular to the composite plate display anisotropy with respect to the direction of stretching. Temperature dependences of magnetization for all samples display difference between zero-field cooled and field-cooled curves of magnetization. This divergence confirms the presence of magnetic interactions in the material. The atomic force microscopy study of the composites’ surfaces revealed that they are relatively smooth and the nanotubes are aligned with the axis of stretching to some extent. 

Russian and Eastern European Dynamic Conditional Correlations in light of the Russian crisis of 2014-2015

This thesis studies the impact of the latest Russian crisis on global markets, and especially Central and Eastern Europe. The results are compared to other shocks and crises over the last twenty years to see how significant they have been. The cointegration process of Central and Eastern European financial markets is also reviewed and updated. Using three separate conditional correlation GARCH models, the latest crisis is not found to have initiated similar surges in conditional correlations to previous crises over the last two decades. Market cointegration for Central and Eastern Europe is found to have stalled somewhat after initial correlation increases post EU accession.

Conceptualizing and counteracting the bullying dynamic: Classroom and school contexts matter

Guided by the social-ecological conceptualization of bullying, this thesis examines the implications of classroom and school contexts—that is, students’ shared microsystems—for peer-to-peer bullying and antibullying practices. Included are four original publications, three of which are empirical studies utilizing data from a large Finnish sample of students in the upper grade levels of elementary school. Both self- and peer reports of bullying and victimization are utilized, and the hierarchical nature of the data collected from students nested within school ecologies is accounted for by multilevel modeling techniques. The first objective of the thesis is to simultaneously examine risk factors for victimization at individual, classroom, and school levels (Study I). The second objective is to uncover the individual- and classroom-level working mechanisms of the KiVa antibullying program which has been shown to be effective in reducing bullying problems in Finnish schools (Study II). Thirdly, an overview of the extant literature on classroom- and school-level contributions to bullying and victimization is provided (Study III). Finally, attention is paid to the assessment of victimization and, more specifically, to how the classroom context influences the concordance between self- and peer reports of victimization (Study IV). Findings demonstrate the multiple ways in which contextual factors, and importantly students’ perceptions thereof, contribute to the bullying dynamic and efforts to counteract it. Whereas certain popular beliefs regarding the implications of classroom and school contexts do not receive support, the role of peer contextual factors and the significance of students’ perceptions of teachers’ attitudes toward bullying are highlighted. Directions for future research and school-based antibullying practices are suggested.

The Nature of Object of Perception and Its Role in the Knowledge Concerning the External World

Questions concerning perception are as old as the field of philosophy itself. Using the first-person perspective as a starting point and philosophical documents, the study examines the relationship between knowledge and perception. The problem is that of how one knows what one immediately perceives. The everyday belief that an object of perception is known to be a material object on grounds of perception is demonstrated as unreliable. It is possible that directly perceived sensible particulars are mind-internal images, shapes, sounds, touches, tastes and smells. According to the appearance/reality distinction, the world of perception is the apparent realm, not the real external world. However, the distinction does not necessarily refute the existence of the external world. We have a causal connection with the external world via mind-internal particulars, and therefore we have indirect knowledge about the external world through perceptual experience. The research especially concerns the reasons for George Berkeley’s claim that material things are mind-dependent ideas that really are perceived. The necessity of a perceiver’s own qualities for perceptual experience, such as mind, consciousness, and the brain, supports the causal theory of perception. Finally, it is asked why mind-internal entities are present when perceiving an object. Perception would not directly discern material objects without the presupposition of extra entities located between a perceiver and the external world. Nevertheless, the results show that perception is not sufficient to know what a perceptual object is, and that the existence of appearances is necessary to know that the external world is being perceived. However, the impossibility of matter does not follow from Berkeley’s theory. The main result of the research is that singular knowledge claims about the external world never refer directly and immediately to the objects of the external world. A perceiver’s own qualities affect how perceptual objects appear in a perceptual situation.

Fiber-reinforced composite fixed dental prostheses: Studies of the materials used as pontics

Fiber-reinforced composite fixed dental prostheses – Studies of the materials used as pontics University of Turku, Faculty of Medicine, Institute of Dentistry, Department of Biomaterials Science, Finnish Doctoral Program in Oral Sciences – FINDOS, Annales Universitatis Turkuensis, Turku, Finland 2015 Fiber-reinforced composites (FRC), a non-metallic biomaterial, represent a suitable alternative in prosthetic dentistry when used as a component of fixed dental prostheses (FDPs). Some drawbacks have been identified in the clinical performance of FRC restorations, such as delamination of the veneering material and fracture of the pontic. Therefore, the current series of studies were performed to investigate the possibilities of enhancing the mechanical and physical properties of FRC FDPs by improving the materials used as pontics, to then heighten their longevity. Four experiments showed the importance of the pontic design and surface treatment in the performance of FRC FDPs. In the first, the load-bearing capacities of inlay-retained FRC FDPs with pontics of various materials and thicknesses were evaluated. Three different pontic materials were assessed with different FRC framework vertical positioning. Thicker pontics showed increased load-bearing capacities, especially ceramic pontics. A second study was completed investigating the influence of the chemical conditioning of the ridge-lap surface of acrylic resin denture teeth on their bonding to a composite resin. Increased shear bond strength demonstrated the positive influence of the pretreatment of the acrylic surfaces, indicating dissolution of the denture surfaces, and suggesting potential penetration of the monomer systems into the surface of denture teeth. A third study analyzed the penetration depth of different monomer systems on the acrylic resin denture teeth surfaces. The possibility of establishing a durable bond between acrylic pontics and FRC frameworks was demonstrated by the ability of monomers to penetrate the surface of acrylic resin denture teeth, measured by a confocal scanning type microscope. A fourth study was designed to evaluate the load-bearing capacities of FRC FDPs using the findings of the previous three studies. In this case, the performance of pre-shaped acrylic resin denture teeth used as pontics with different composite resins as filling materials was evaluated. The filling material influenced the load-bearing capacities, providing more durable FRC FDPs. It can be concluded that the mechanical and physical properties of FRC FDPs can be improved as has been shown in the development of this thesis. The improvements reported then might provide long lasting prosthetic solutions of this kind, positioning them as potentially permanent rehabilitation treatments. Key words: fiber-reinforced composite, fixed dental prostheses, inlay-retained bridges, adhesion, acrylic resin denture teeth, dental material.

Generative Part-Based Gabor Object Detector

Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.