Literature review on permanent magnet generators design and dynamic behavior

This paper is a literature review which describes the construction of state of the art of permanent magnet generators and motors constructing and discusses the current and possible application of these machines in industry. Permanent magnet machines are a well-know class of rotating and linear electric machines used for many years in industrial applications. A particular interest for permanent magnet generators is connected with wind mills, which seem to be becoming increasingly popular nowadays. Geared and direct-driven permanent magnet generators are described. A classification of direct-driven permanent magnet generators is given. Design aspects of permanent magnet generators are presented. Permanent magnet generators for wind turbines designs are highlighted. Dynamics and vibration problems of permanent magnet generators covered in literature are presented. The application of the Finite Element Method for mechanical problems solution in the field of permanent magnet generators is discussed.

Dimensioning DC-voltage capacitor for a DC-distribution system and dynamic analysis

Technical analysis of Low Voltage Direct Current (LVDC) distribution systems shows that in LVDC transmission the customer voltage quality is higher. One of the problems in LVDC distribution networks that converters both ends of the DC line are required. Because of the converters produce not pure DC voltage, but some fluctuations as well, the huge electrolytic capacitors are required to reduce voltage distortions in the DC-side. This thesis master’s thesis is focused on calculating required DC-link capacitance for LVDC transmission and estimation of the influence of different parameters on the voltage quality. The goal is to investigate the methods of the DC-link capacitance estimation and location in the transmission line.

Dynamic patterns of flow in the workplace: characterizing within-individual variability using a complexity science approach

As a result of the growing interest in studying employee well-being as a complex process that portrays high levels of within-individual variability and evolves over time, this present study considers the experience of flow in the workplace from a nonlinear dynamical systems approach. Our goal is to offer new ways to move the study of employee well-being beyond linear approaches. With nonlinear dynamical systems theory as the backdrop, we conducted a longitudinal study using the experience sampling method and qualitative semi-structured interviews for data collection; 6981 registers of data were collected from a sample of 60 employees. The obtained time series were analyzed using various techniques derived from the nonlinear dynamical systems theory (i.e., recurrence analysis and surrogate data) and multiple correspondence analyses. The results revealed the following: 1) flow in the workplace presents a high degree of within-individual variability; this variability is characterized as chaotic for most of the cases (75%); 2) high levels of flow are associated with chaos; and 3) different dimensions of the flow experience (e.g., merging of action and awareness) as well as individual (e.g., age) and job characteristics (e.g., job tenure) are associated with the emergence of different dynamic patterns (chaotic, linear and random).

A dynamic analysis of asymmetric shocks in EU manufacturing

Available empirical evidence regarding the degree of symmetry between European economies in the context of Monetary Unification is not conclusive. This paper offers new empirical evidence concerning this issue related to the manufacturing sector. Instead of using a static approach as most empirical studies do, we analyse the dynamic evolution of shock symmetry using a state-space model. The results show a clear reduction of asymmetries in terms of demand shocks between 1975 and 1996, with an increase in terms of supply shocks at the end of the period.

Dynamic electrostatic force microscopy in liquid media

We present the implementation of dynamic electrostatic force microscopy in liquid media. This implementation enables the quantitative imaging of local dielectric properties of materials in electrolyte solutions with nanoscale spatial resolution. Local imaging capabilities are obtained by probing the frequency-dependent and ionic concentration-dependent electrostatic forces at high frequency (>1 MHz), while quantification of the interaction forces is obtained with finite-element numerical calculations. The results presented open a wide range of possibilities in a number of fields where the dielectric properties of materials need to be probed at the nanoscale and in a liquid environment.

Dynamic electrostatic force microscopy in liquid media

We present the implementation of dynamic electrostatic force microscopy in liquid media. This implementation enables the quantitative imaging of local dielectric properties of materials in electrolyte solutions with nanoscale spatial resolution. Local imaging capabilities are obtained by probing the frequency-dependent and ionic concentration-dependent electrostatic forces at high frequency (>1 MHz), while quantification of the interaction forces is obtained with finite-element numerical calculations. The results presented open a wide range of possibilities in a number of fields where the dielectric properties of materials need to be probed at the nanoscale and in a liquid environment.

Creating dynamic continuous improvement system for Larox Corporation

Today´s organizations must have the ability to react to rapid changes in the market. These rapid changes cause pressure to continuously find new efficient ways to organize work practices. Increased competition requires businesses to become more effective and to pay attention to quality of management and to make people to understand their work's impact on the final result. The fundamentals in continmuois improvement are systematic and agile tackling of indentified individual process constraints and the fact tha nothin finally improves without changes. Successful continuous improvement requires management commitment, education, implementation, measurement, recognition and regeneration. These ingredients form the foundation, both for breakthrough projects and small step ongoing improvement activities. One part of the organization's management system are the quality tools, which provide systematic methodologies for identifying problems, defining their root causes, finding solutions, gathering and sorting of data, supporting decision making and implementing the changes, and many other management tasks. Organizational change management includes processes and tools for managing the people in an organizational level change. These tools include a structured approach, which can be used for effective transition of organizations through change. When combined with the understanding of change management of individuals, these tools provide a framework for managing people in change,

Programming and analysing measurement experiments using the PicoCricket system

The aim of this project is to get used to another kind of programming. Since now, I used very complex programming languages to develop applications or even to program microcontrollers, but PicoCricket system is the evidence that we don’t need so complex development tools to get functional devices. PicoCricket system is the clear example of simple programming to make devices work the way we programmed it. There’s an easy but effective way to programs mall devices just saying what we want them to do. We cannot do complex algorithms and mathematical operations but we can program them in a short time. Nowadays, the easier and faster we produce, the more we earn. So the tendency is to develop fast, cheap and easy, and PicoCricket system can do it.

Matkustajainformaatiojärjestelmän toteuttaminen junaan

Matkustajainformaatio junassa koostuu vaunujen ulkopuolisilla kylkinäytöillä esitettävistä junan lähtö-, väli- ja määräasematiedoista yhdessä junan ja vaunujen myyntinumeroiden kanssa sekä vaunujen sisäpuolella automaattisista kuulutuksista ja matkustamon näytöillä esitettävästä staattisesta ja vaihtuvasta informaatiosta. Työssä toteutetaan matkustajainformaatiojärjestelmä käytettäväksi matkustajunissa. Järjestelmään syötetään ennen matkan alkua junan tiedot, jonka jälkeen se toimii automaattisesti ilman tarvetta junahenkilökunnan toimenpiteille. Poikkeustilanteissa junahenkilökunta voi estää järjestelmän toiminnan tai valita esiohjelmointuja erikoiskuulutuksia. Toteuttamismenetelmäksi valittiin C-ohjelmointikieli Linux-käyttöjärjestelmällä varustetulla sulautetulla rautatiekäyttöön suunnitellulla laitealustalla.

Comparison Structure Analysis

This study presents an automatic, computer-aided analytical method called Comparison Structure Analysis (CSA), which can be applied to different dimensions of music. The aim of CSA is first and foremost practical: to produce dynamic and understandable representations of musical properties by evaluating the prevalence of a chosen musical data structure through a musical piece. Such a comparison structure may refer to a mathematical vector, a set, a matrix or another type of data structure and even a combination of data structures. CSA depends on an abstract systematic segmentation that allows for a statistical or mathematical survey of the data. To choose a comparison structure is to tune the apparatus to be sensitive to an exclusive set of musical properties. CSA settles somewhere between traditional music analysis and computer aided music information retrieval (MIR). Theoretically defined musical entities, such as pitch-class sets, set-classes and particular rhythm patterns are detected in compositions using pattern extraction and pattern comparison algorithms that are typical within the field of MIR. In principle, the idea of comparison structure analysis can be applied to any time-series type data and, in the music analytical context, to polyphonic as well as homophonic music. Tonal trends, set-class similarities, invertible counterpoints, voice-leading similarities, short-term modulations, rhythmic similarities and multiparametric changes in musical texture were studied. Since CSA allows for a highly accurate classification of compositions, its methods may be applicable to symbolic music information retrieval as well. The strength of CSA relies especially on the possibility to make comparisons between the observations concerning different musical parameters and to combine it with statistical and perhaps other music analytical methods. The results of CSA are dependent on the competence of the similarity measure. New similarity measures for tonal stability, rhythmic and set-class similarity measurements were proposed. The most advanced results were attained by employing the automated function generation – comparable with the so-called genetic programming – to search for an optimal model for set-class similarity measurements. However, the results of CSA seem to agree strongly, independent of the type of similarity function employed in the analysis.

Learning Robot Motions from Visual Sensing

Learning from demonstration becomes increasingly popular as an efficient way of robot programming. Not only a scientific interest acts as an inspiration in this case but also the possibility of producing the machines that would find application in different areas of life: robots helping with daily routine at home, high performance automata in industries or friendly toys for children. One way to teach a robot to fulfill complex tasks is to start with simple training exercises, combining them to form more difficult behavior. The objective of the Master’s thesis work was to study robot programming with visual input. Dynamic movement primitives (DMPs) were chosen as a tool for motion learning and generation. Assuming a movement to be a spring system influenced by an external force, making this system move, DMPs represent the motion as a set of non-linear differential equations. During the experiments the properties of DMP, such as temporal and spacial invariance, were examined. The effect of the DMP parameters, including spring coefficient, damping factor, temporal scaling, on the trajectory generated were studied.

Thermal behaviour of succinic acid, sodium succinate and its compounds with some bivalent transitions metal ions in dynamic N2 and CO2 atmospheres

Thermal stability and thermal decomposition of succinic acid, sodium succinate and its compounds with Mn(II), Fe(II), Co(II), Ni(II), Cu(II) and Zn(II) were investigated employing simultaneous thermogravimetry and differential thermal analysis (TG-DTA) in nitrogen and carbon dioxide atmospheres and TG-FTIR in nitrogen atmosphere. On heating, in both atmospheres the succinic acid melt and evaporate, while for the sodium succinate the thermal decomposition occurs with the formation of sodium carbonate. For the transition metal succinates the final residue up to 1180 ºC in N2 atmosphere was a mixture of metal and metal oxide in no simple stoichiometric relation, except for Zn compound, where the residue was a small quantity of carbonaceous residue. For the CO2 atmosphere the final residue up to 980 ºC was: MnO, Fe3O4, CoO, ZnO and mixtures of Ni, NiO and Cu, Cu2O.

Promoting Programming Learning. Engagement, Automatic Assessment with Immediate Feedback in Visualizations

The skill of programming is a key asset for every computer science student. Many studies have shown that this is a hard skill to learn and the outcomes of programming courses have often been substandard. Thus, a range of methods and tools have been developed to assist students’ learning processes. One of the biggest fields in computer science education is the use of visualizations as a learning aid and many visualization based tools have been developed to aid the learning process during last few decades. Studies conducted in this thesis focus on two different visualizationbased tools TRAKLA2 and ViLLE. This thesis includes results from multiple empirical studies about what kind of effects the introduction and usage of these tools have on students’ opinions and performance, and what kind of implications there are from a teacher’s point of view. The results from studies in this thesis show that students preferred to do web-based exercises, and felt that those exercises contributed to their learning. The usage of the tool motivated students to work harder during their course, which was shown in overall course performance and drop-out statistics. We have also shown that visualization-based tools can be used to enhance the learning process, and one of the key factors is the higher and active level of engagement (see. Engagement Taxonomy by Naps et al., 2002). The automatic grading accompanied with immediate feedback helps students to overcome obstacles during the learning process, and to grasp the key element in the learning task. These kinds of tools can help us to cope with the fact that many programming courses are overcrowded with limited teaching resources. These tools allows us to tackle this problem by utilizing automatic assessment in exercises that are most suitable to be done in the web (like tracing and simulation) since its supports students’ independent learning regardless of time and place. In summary, we can use our course’s resources more efficiently to increase the quality of the learning experience of the students and the teaching experience of the teacher, and even increase performance of the students. There are also methodological results from this thesis which contribute to developing insight into the conduct of empirical evaluations of new tools or techniques. When we evaluate a new tool, especially one accompanied with visualization, we need to give a proper introduction to it and to the graphical notation used by tool. The standard procedure should also include capturing the screen with audio to confirm that the participants of the experiment are doing what they are supposed to do. By taken such measures in the study of the learning impact of visualization support for learning, we can avoid drawing false conclusion from our experiments. As computer science educators, we face two important challenges. Firstly, we need to start to deliver the message in our own institution and all over the world about the new – scientifically proven – innovations in teaching like TRAKLA2 and ViLLE. Secondly, we have the relevant experience of conducting teaching related experiment, and thus we can support our colleagues to learn essential know-how of the research based improvement of their teaching. This change can transform academic teaching into publications and by utilizing this approach we can significantly increase the adoption of the new tools and techniques, and overall increase the knowledge of best-practices. In future, we need to combine our forces and tackle these universal and common problems together by creating multi-national and multiinstitutional research projects. We need to create a community and a platform in which we can share these best practices and at the same time conduct multi-national research projects easily.

Early nutritional determinants in cardio-metabolic programming – A prospective randomized controlled dietary intervention study

Western societies have been faced with the fact that overweight, impaired glucose regulation and elevated blood pressure are already prevalent in pediatric populations. This will inevitably mean an increase in later manifestations of cardio-metabolic diseases. The dilemma has been suggested to stem from fetal life and it is surmised that the early nutritional environment plays an important role in the process called programming. The aim of the present study was to characterize early nutritional determinants associating with cardio-metabolic risk factors in fetuses, infants and children. Further, the study was designated to establish whether dietary counseling initiated in early pregnancy can modify this cascade. Healthy mother-child pairs (n=256) participating in a dietary intervention study were followed from early pregnancy to childhood. The intervention included detailed dietary counseling by a nutritionist targeting saturated fat intake in excess of recommendations and fiber consumption below recommendations. Cardio-metabolic programming was studied by characterizing the offspring’s cardio-metabolic risk factors such as over-activation of the autonomic nervous system, elevated blood pressure and adverse metabolic status (e.g. serum high split proinsulin concentration). Fetal cardiac sympathovagal activation was measured during labor. Postnatally, children’s blood pressure was measured at six-month and four-year follow-up visits. Further, infants’ metabolic status was assessed by means of growth and serum biomarkers (32-33 split proinsulin, leptin and adiponectin) at the age of six months. This study proved that fetal cardiac sympathovagal activity was positively associated with maternal pre-pregnancy body mass index indicating adverse cardio-metabolic programming in the offspring. Further, a reduced risk of high split proinsulin in infancy and lower blood pressure in childhood were found in those offspring whose mothers’ weight gain and amount and type of fats in the diet during pregnancy were as recommended. Of note, maternal dietary counseling from early pregnancy onwards could ameliorate the offspring’s metabolic status by reducing the risk of high split proinsulin concentration, although it had no effect on the other cardio-metabolic markers in the offspring. At postnatal period breastfeeding proved to entail benefits in cardio-metabolic programming. Finally, the recommended dietary protein and total fat content in the child’s diet were important nutritional determinants reducing blood pressure at the age of four years. The intrauterine and immediate postnatal period comprise a window of opportunity for interventions aiming to reduce the risk of cardio-metabolic disorders and brings the prospect of achieving health benefits over one generation.