Perceptual features are qualitative features used to describe music properties in relation to human perception instead of typical musical theory concepts such as pitches and chords. This report describes a music discovery platform which uses three different methods of music playlist generation to investigate if and how perceptual features work when used for music discovery. One method abstracts away the complexity of perceptual features and the other two lets users use them directly. Two user testing sessions were performed to evaluate the browser and compare the different methods. Test participants found the playlist generation to work well in general, and especially found the method which uses emotions as an interface to be intuitive, enjoyable and something they would use to find new music. The other two methods which let users directly interact with perceptual features were less popular, especially among users without musical education. Overall, using perceptual features for music discovery was successful, although methods should be chosen with the intended audience in mind. / Perceptuella särdrag är kvalitativt framtagna särdrag som beskriver musik med fokus på mänsklig perception snarare än musikteoribegrepp som tonhöjd och ackord. Den här rapporten beskriver en musikhemsida som använder tre olika metoder för att generera spellistor med avsikt att undersöka om och hur perceptuella särdrag fungerar för att hitta ny musik. En metod abstraherar bort perceptuella särdragens komplexitet och de andra två metoderna låter testare använda dem utan abstraktion. Två användbarhetstest utfördes för att utvärdera musikhemsidan och jämföra de olika metoderna. Testanvändare tyckte överlag att genereringen av spellistor fungerade bra och att speciellt metoden som använde känslor som gränssnitt var intuitiv, rolig att använda och en metod de skulle använda för att hitta ny musik. De andra två metoderna som tillät användare att direkt använda perceptuella särdrag var mindre populära, speciellt bland användare utan musikutbildning. Överlag var användandet av perceptuella särdrag för att hitta musik en framgång, dock bör metoderna väljas utifrån användarnas kunskap.

All three shape marks-exclusions in EUTMR art. 7 e) can be avoided by adding an essential element to a shape, which is not attributable to the conditions set out in the exclusions, such as a distinctive nonfunctional element. A valid shape mark registration gives the rights holder the right to prevent other trade mark registrations of identical or similar signs for identical or similar goods if there exists a likelihood of confusion on the part of the public, as well as to initiate infringement proceedings against anyone who uses such a sign in their line of business. Under the test for likelihood of confusion, it is assessed to what extent the average consumer remembers a distinctive sign, which is not limited to its distinctive elements. Since the average consumer is capable to remember other elements than distinctive elements, only negligible elements are excluded from the average consumer’s overall perception of the sign. Non-distinctive elements are not necessarily deemed negligible, depending on their size and/or position within the mark. So, while functional elements are usually perceived as merely functional or ornamental, and thus non-distinctive, they may still be deemed non-negligible due to their size and/or position within the mark. Case law shows that a likelihood of confusion may therefore follow as a result of two marks only sharing an element deemed non-distinctive on its own. The CJEU has also expressed that the public interest behind the test for likelihood of confusion is to secure the rights holder’s interests and not to secure the competitors’ need for a free access to signs and elements. The need to keep certain signs and elements free is therefore not considered a relevant factor in the test for likelihood of confusion. So, while it may seem logical that a sign, which is registrable only due to incorporating a distinctive element as a part of a complex mark, would have a scope of protection limited only to that distinctive element, case law shows that such a conclusion is not necessarily true. In this thesis it is argued that if the average consumer does not even perceive that a functional element constitutes a part of a complex decorated shape mark, consisting of both e.g. a functional naked shape and the added distinctive element, the functional element is negligible and will not be remembered by the average consumer. But if the average consumer is able to perceive a functional naked shape or element as its own indication of origin, or at least as an element of such a complex mark, its size and position alone in the complex mark could be enough to be able to establish a similarity of signs with another resembling shape, even if the latter lacks the inclusion of the same distinctive element. If the other shape does not deviate enough from the visual appearance of the functional naked shape or element in the registered complex mark, the similarity of the signs could be enough to cause a likelihood of confusion.

En utgångspunkt för den föreliggande avhandlingen och doktorsstudien är den spridning och ökning av projektarbetsformens tillämpning, som skett sedan mitten av 1900-talet. Det har blivit allt vanligare med så kallade multiprojektmiljöer, dvs. verksamheter där projekt är en normalt förkommande arbetsform och av så stor betydelse att projektledning och projektstyrning (t.ex. värdering och uppföljning av projekt) är en viktig fråga för organisationens ledning. För många organisationer där förmågan att hantera projektarbetsformen blivit avgörande för överlevnad och lönsamhet finns därför ett stort behov av att förbättra projekthanteringen. Det dominerande synsättet har länge varit att alla projekt i grunden är likartade och kan ledas och styras effektivt med standardiserade projektledningstekniker och modeller. Alltfler forskare menar dock att det är så stora skillnader mellan olika projekttyper att projekthanteringen måste anpassas efter projektens särdrag, vilket förutsätter en möjlighet att analysera det aktuella projektet – att kunna ställa en ”projektdiagnos”. I en ambition att öka kunskapen om projekten i sig, är syftet med doktorsstudien att utveckla beskrivningar av de särdrag i projekt som har avgörande betydelse för projekthantering i multiprojektmiljöer. Tre fallstudier har genomförts i tre organisationer som utvecklat och implementerat en projektmodell för att förbättra sin projekthantering. Fallstudierna har delvis genomförts med aktionsforskning som metod. Detta har gjort det möjligt att studera projekthanteringen under lång tid, och att skapa nyanserade beskrivningar av särdragen i respektive multiprojektmiljö. Utifrån fallstudierna, projektforskningen och egna erfarenheter från projektmiljöer, har ett ramverk för strukturerad projektanalys utformats i syfte att öka resultatens generaliserbarhet. Ramverket, som består av tre analysmodeller och tre grundläggande perspektiv på projekt, utgör en begreppsapparat för strukturerad projektanalys som är fristående från fallstudierna. Studien visar hur särdragen i olika projekttyper, t.ex. förekomsten av dubbla operativa logiker och olika slag av komplexitet, är avgörande dels för projekthanteringen, dels för vilka förbättringsåtgärder som är effektiva i en multiprojektmiljö. Ytterligare ett bidrag från studien är det ramverk som utformats med utgångspunkt i den stora variation som olika projekt uppvisar ur ett resultatperspektiv. / A starting point for the present thesis is the increased application of the project work form, a form that has been growing in usage since the mid 1900s. Today, multiproject environments have become increasingly common, i.e. organisations where projects are a normal part of the working environment and where they are of such great importance that project management and project steering (e.g. evaluation and follow-up) are considered important for the organisation's management. In many organisations where the ability to apply the project work form is critical for survival and profitability, there is a great need to improve the management of projects. The dominating view has long been that all projects are inherently alike, and can be effectively managed and controlled with standardised project management techniques and models. However, more and morere searchers are pointing out that because there are in fact quite distinct differences between different types of projects, project management must be adapted to the distinctive characteristics of the project, which presupposes the possibility of analysing the project in question – of being able to make a "project diagnosis". In an attempt to increase knowledge about projects as a type of work form, this doctoral study aims to develop descriptions of distinctive characteristics in projects that are essential for project management in multiproject environments. Three case studies have been performed in three organisations that have developed and implemented a project model to improve their project management. The case studies have been performed using action research methodology. This has made it possible to study project management during an extended period of time, creating nuanced descriptions of the distinctive characteristics in each multiproject environment. From the case studies, project research and personal experience in project environments, a framework for Structured Project Analysis (SPA) has been designed with the aim of increasing the generalisation of the results. The framework, based on three analysis models and three basic perspectives of projects, provides a conceptual model for structured project analysis independent of the case studies. The study shows how the various distinctive characteristics of different project types, such as the presence of dual operational logics and varying types of complexity, are crucial for both management of projects and for deciding which improvement measures are most effective in a multiproject environment. A further contribution of the study is the framework that has been designed based on the wide variation presented by different projects through a results perspective.

Radar signals are used for estimating location, speed and direction of an object. Some radars emit pulses, while others emit a continuous wave. Both types of radars emit signals according to some pattern; a pulse radar, for example, emits pulses with a specific time interval between pulses. This time interval may either be stable, change linearly, or follow some other pattern. The interval between two emitted pulses is often referred to as the pulse repetition interval (PRI), and the pattern that defines the PRI is often referred to as the modulation. Classifying which PRI modulation is used in a radar signal is a crucial component for the task of identifying who is emitting the signal. Incorrectly classifying the used modulation can lead to an incorrect guess of the identity of the agent emitting the signal, and can as a consequence be fatal. This work investigates how a long short-term memory (LSTM) neural network performs compared to a state of the art feature extraction neural network (FE-MLP) approach for the task of classifying PRI modulation. The results indicate that the proposed LSTM model performs consistently better than the FE-MLP approach across all tested noise levels. The downside of the proposed LSTM model is that it is significantly more complex than the FE-MLP approach. Future work could investigate if the LSTM model is too complex to use in a real world setting where computing power may be limited. Additionally, the LSTM model can, in a trivial manner, be modified to support more modulations than those tested in this work. Hence, future work could also evaluate how the proposed LSTM model performs when support for more modulations is added. / Radarsignaler används för att uppskatta plats, hastighet och riktning av objekt. Vissa radarer sänder ut signaler i form av pulser, medan andra sänder ut en kontinuerlig våg. Båda typer av radarer avger signaler enligt ett visst mönster, till exempel avger en pulsradar pulser med ett specifikt tidsintervall mellan pulserna. Detta tidsintervall kan antingen vara konstant, förändras linjärt, eller följa ett annat mönster. Intervallet mellan två pulser benämns ofta pulsrepetitionsintervall (PRI), och mönstret som definierar PRIn benämns ofta modulering. Att klassificera vilken PRI-modulering som används i en radarsignal är en viktig del i processen att identifiera vem som skickade ut signalen. Felaktig klassificering av den använda moduleringen kan leda till en felaktig gissning av identiteten av agenten som skickade ut signalen, vilket kan leda till ett dödligt utfall. Detta arbete undersöker hur väl det framtagna neurala nätverket som består av ett långt korttidsminne (LSTM) kan klassificera PRI-modulering i förhållande till en modern modell som använder särskilt utvalda beräknade särdrag från data och klassificerar dessa särdrag med ett neuralt nätverk. Resultaten indikerar att LSTM-modellen konsekvent klassificerar med högre träffsäkerhet än modellen som använder särdrag, vilket gäller för alla testade brusnivåer. Nackdelen med LSTM-modellen är att den är mer komplex än modellen som använder särdrag. Framtida arbete kan undersöka om LSTM-modellen är för komplex för att använda i ett verkligt scenario där beräkningskraften kan vara begränsad. Dessutom skulle framtida arbete kunna utvärdera hur väl LSTM-modellen kan klassificera PRI-moduleringar när stöd för fler moduleringar än de som testats i detta arbete läggs till, detta då stöd för ytterligare PRI-moduleringar kan läggas till i LSTM-modellen på ett trivialt sätt.

Visual tracking is a computer vision problem where the task is to follow a targetthrough a video sequence. Tracking has many important real-world applications in several fields such as autonomous vehicles and robot-vision. Since visual tracking does not assume any prior knowledge about the target, it faces different challenges such occlusion, appearance change, background clutter and scale change. In this thesis we try to improve the capabilities of tracking frameworks using discriminative correlation filters by incorporating scene depth information. We utilize scene depth information on three main levels. First, we use raw depth information to segment the target from its surroundings enabling occlusion detection and scale estimation. Second, we investigate different visual features calculated from depth data to decide which features are good at encoding geometric information available solely in depth data. Third, we investigate handling missing data in the depth maps using a modified version of the normalized convolution framework. Finally, we introduce a novel approach for parameter search using genetic algorithms to find the best hyperparameters for our tracking framework. Experiments show that depth data can be used to estimate scale changes and handle occlusions. In addition, visual features calculated from depth are more representative if they were combined with color features. It is also shown that utilizing normalized convolution improves the overall performance in some cases. Lastly, the usage of genetic algorithms for hyperparameter search leads to accuracy gains as well as some insights on the performance of different components within the framework.