Tato disertační práce je zaměřena na analýzu řečového signálu za učelem detekce nemocí ovlivňujících strukturu hlasových orgánů, obzvláště těch, které mění strukturální character hlasivek. Poskytnut je přehled současných technik. Dále jsou popsány zdroje použitých nahrávek pro zdravé a nemocné mlučí. Hlavním učelem této disertační práce je popsat vypočetní postup k odhadu parametrů modelu hlasového zdroje, které umožní následnou detekci a klasifikaci nemocí hlasivek. Poskytujeme detailní popis analýzy řečových signálů, které mohou být odvozeny z parametrických modelů hlasivek.

In electronic warfare, one of the key technologies is radar. Radar is used to detect and identify unknown aerial, nautical or land-based objects. An attribute of of a pulsed radar signal is the Pulse Repetition Interval (PRI) which is the time interval between pulses in a pulse train. In a passive radar receiver system, the PRI can be used to recognize the emitter system. Correct classification of emitter systems is a crucial part of Electronic Support Measures (ESM) and Radar Warning Receivers (RWR) in order to deploy appropriate measures depending on the emitter system. Inaccurate predictions of emitter systems can have lethal consequences and variables such as time and confidence in the predictions are essential for an effective predictive method. Due to the classified nature of military systems and techniques, there are no industry standard systems or techniques that perform quick and accurate classifications of emitter systems based on PRI. Therefore, methods that allows for fast and accurate predictions based on PRI is highly desirable and worthy of research. This thesis explores and compares the capabilities of two machine learning methods for the task of classifying emitters based on received PRI. The first method is an attention based model which performs well throughout all levels of realistic noise and is quick to learn and even quicker to give accurate predictions. The second method is a K-Nearest Neighbor (KNN) implementation that, while performing well for noise-free PRI, finds its performance degrading as the amount of noise increases. An additional outcome of this thesis is the development of a system to generate samples in an automated fashion. The attention based model performs well, achieving a macro avarage F1-score of 63% in the 59-class recognition task whereas the performance of the KNN is lower, achieving a macro avarage F1-score of 43%. Future research could be conducted with the purpose of designing a better attention based model for producing higher and more confident predictions and designing algorithms to reduce the time complexity of the KNN implementation. / En av de viktigaste teknikerna inom telektrig är radarn. Radar används för att upptäcka och identifiera okända, luftburna, sjögående eller landbaserade förmål. En komponent av radar är Pulsrepetitionsinterval (Pulse Repetition Intervall, PRI) som beskrivs som tidsintervallet mellan två inkommande pulser. I ett radarvarnar system (Radar Warning Receiver, RWR) kan PRI användas för att identifiera radarsystem. Korrekt identifiering av radarsystem är en viktig uppgift för elektroniska understödsmedel (Electronic Support Measures, ESM) med syfte att tillsätta lämpliga medel beroende på radarsystemet i fråga. Icke tillförlitlig identifiering av radarsystem kan ha dödliga konsekvenser och variabler som tid och säkerhet i identifieringen är avgörande för ett effektivt system. Då dokumentation och specifikationer för militära system i regel är hemligstämplade är det svårt att utröna någon typ av industristandard för att utföra snabb och säker klassificering av radarsystem baserat på PRI. Därför är det av stort intresse detta område och möjligheterna för sådana lösningar utforskas. Detta examensarbete utforskar och jämför förmågorna hos två maskininlärningsmetoder i avseende att korrekt identifiera radarsändare baserat på genererat PRI. Den första metoden är ett djupt neuralt nätverk som använder sig av tekniken ”attention”. Det djupa nätverket presterar bra för alla brusnivåer och lär sig snabbt att känna igen attributen hos PRI som kännetecknar vilken radarsändare och som efter träning dessutom är snabb på att korrekt identifiera PRI. Den andra metoden är en K-Nearest Neighbor implementation som förvisso presterar bra på icke brusig data men vars förmåga försämras allt eftersom brusnivåerna ökar. Ett ytterligare resultat av arbetet är utvecklingen och implementationen av en metod för att specificera PRI och sedan generera PRI efter specifikation. Attention modellen genererar bra prediktioner för data bestående av 59 klasser, med ett F1-score snitt om 63% medan KNN-implementationen för samma uppgift har en lägre träffsäkerhet med ett F1-score snitt om 43%. Vidare forskning kan innefatta utökad utveckling av det djupa, neurala nätverket i syfte att förbättra dess förmåga för identifiering och metoder för att minimera tidsåtgången för KNN implementationen.

The theme of the song Lonely Woman by Ornette Coleman and the song It’s Halloween by The Shaggs has something in common when it comes to how the different instruments relate rhythmically to each other. I would call it a musical quality that could be described as a feeling of ungraspability. I had this quality in focus during a process of listening to music, writing music and playing music. To describe the cause of this quality I felt the need to define two concepts I named 1) rubato structures; rhythmic structures that aren’t based on, nor establish a steady pulse, and 2) tempo structures; rhythmic structures that are based on and establishes a steady pulse. Throughout the project I identified the cause of the quality, to be combinations of rubato structures and tempo structures, however my understanding developed during the project to a more specific definition which was layers of rubato structures and tempo structures. In the 6 compositions that this project resulted in, I created a number of musical situations with my group, which all had these elements. When listed, these situations rather systematically go through ways of combining structures in regards to different parameters. When listened to, at least for me, several of them give rise to the feeling of ungraspability I had in focus. My attempts to describe and analyze the many inspiring examples stretching from Charles Ives to Swedish contemporary vocal folk music, helped me to develope tools for making music of my own, rather than resulting in some objective truth, or a system for describing and analyzing music that would work objectively. One thing I would consider objectively true, however, is that there are a lot of different ways of creating rhythmic complexity, where some ways are very tedious and difficult for the musicians. With rhythmic layers of rather simple structures, containing rubato structures, I can create rhythmic complexity beyond the quantifiable, just by putting the human impulses in control. Takt in Swedish could mean many things, such as beat, meter, bar, measure. Otakt is often used as a negative word to describe a failed attempt to play in time, but is also linguistically the negation of takt (thus meaning no beat, no meter, no bar, no measure). Takt och (and) Otakt is therefor a play with words, since otakt relates to things in this study that is embraced rather than avoided. / <p>Bilaga: CD</p>

Die Elektronen-Spin-Resonanz-Spektroskopie (ESR) in Verbindung mit ortsspezifischer Spinmarkierung stellt eine hervorragende Möglichkeit dar, um die Struktur und Dynamik von Proteinen aufzuklären. In dieser Dissertation wurden mit Hilfe der Hochfeld-ESR-Spektroskopie (W-Band, 95 GHz, T=160 K) für dreizehn spinmarkierte Colicin A Proben die Polarität und die Protizität der Umgebung der Spinlabelbindestelle bestimmt. Wasserzugänglichkeiten und Wasserstoffbrückenbindungen zum Spinlabel wurden mittels Puls-ESR Methoden (3-Puls-D-ESEEM und Hahn-Echozerfall) bestimmt und die Ergebnisse mit den Polaritäts- und Protizitätswerten korreliert. Raumtemperaturspektren dieser Proben im X-Band (9.5 GHz), Q-Band (34 GHz) und W-Band (95 GHz) liefern Informationen über die Spinlabelbewegung. Mit Hilfe von Molekulardynamiksimulationen (MD) der spinmarkierten kanalbildenden Domäne von Colicin A konnten die Konformationen (Rotameranalyse) und die Dynamik der Spinlabelseitenketten in den unterschiedlichen Umgebungen charakterisiert werden. Der Vergleich der experimentellen mit den aus MD-Trajektorien berechneten ESR-Spektren liefert die Beiträge der unterschiedlichen Rotamerübergänge, die für die beobachteten Spektrenformen charakteristisch sind.

The master thesis is focused on the simulation of the toroid coils in Ansoft Maxwell 3D software, which uses finite element method for electromagnetic field simulation. Firstly the process creation of the geometric model toroid coil with seventy-five threaded is presented. It is necessary to debug this model and prepare it for the mesh generation. Physical properties are assign to this model and it gives rise to the physical model. We will set boundaries, excitation current, core material, winding material and the parameters for the mesh generations. New material Kashke K4000 will be created in the materials library and subsequently we will define its BH curve on the basis of datasheet. Analysis is made in two modes. Direct currents (7,5A; 10A; 15A; 20A; 25A) and (non)linear materials are used in magnetostatic solution. Toroid coil is excited by current pulse in transient solution. In Ansoft Maxwell Circuit editor a source which generates current pulse will be created. This excitation will be assigned to the toroid coil as an extern source through a terminal. Core material is linear in the case of transient analysis, because Ansoft Maxwell 3D doesn´t allow to use nonlinear material in this solution. Settings are different in transient and in magnetostatic analysis. End time and time step are entered to solve this task in transient analysis. Time points are entered too. Flux density and electromagnetic field strength are calculated in these time points and later it will be possible to view the results. Calculated fields are shown as the pictures in this thesis. The procedure how to use a field calculator in the postprocessing is given as well. The achievements are summarized in the conclusion.