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3. Dreamer : live coding, algorave and the artistic exploration of dreamsLazar Mihajlović, 2024, master's thesis Abstract: Observing the developments and intersections between music, graphics, video, code and club culture in the music scene around the year 2010, primarily based in England, a new cultural movement known as ”Algorave” has emerged, reshaping the boundaries of new artistic expression. While the practices of live and creative coding had been present on the global stage for some time, the “Algorave” scene emerges as a unique blend of these artistic directions, combining various elements and offering a distinctive sound-visual artistic expression. Unlike traditional music performances, artists of this movement openly share their live coding processes with the audience, guiding them through the entire process of the performance. By utilizing live coding as the primary artistic tool and integrating it with artificial intelligence, the work Dreamer demonstrates a fusion of these two approaches. It visually explores dreams using images generated by AI technology. These images are then manipulated through live coding techniques, creating a visual narrative that is accompanied by ambient-electronic sounds. The sound complements the visual elements, achieved through the use of various synthesizers, samplings and granular synthesis, a technique that fragments sound into small grains to create complex sound textures. Beyond its practical execution, Dreamer addresses dreams as something unknown and undisclosed. It raises the question of whether dreams can be considered insights into our parallel lives, or are they merely products of our imagination? Should we explore them rather than just observe them? Based on these questions, the work examines dreams through programming and technology, seeking new possibilities for artistic expression.
Keywords: code, sound, algorithm, visual art, algorave, technology, master's thesis
Published in RUNG: 03.10.2024; Views: 1366; Downloads: 9
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4. Search for a signal from dark matter sub-halos with the galactic plane survey of CTA Observatory : master's thesisZoja Rokavec, 2024, master's thesis Abstract: Dark matter (DM), known to be a dominant matter component in the Universe,
has been searched for extensively, yet remains undetected. One of the promising
avenues of detecting a DM signal is to observe the so called ’DM sub-halos’ within
our galaxy. These sub-halos, which are numerous within the Milky Way, are formed
by the clustering of DM, as predicted by cosmological simulations, and most of
them lack baryonic matter counterparts, making them challenging to detect. How-
ever, the annihilation or decay of Weakly Interacting Massive Particles (WIMPs),
a leading candidate for DM, within these sub-halos is expected to produce very
high-energy (VHE) photons (called gamma-rays) at TeV energies, offering possible
indirect DM detection.
In this thesis, we focus on the Galactic Plane Survey (GPS) of the Cherenkov Tele-
scope Array Observatory (CTAO), an upcoming ground-based gamma-ray obser-
vatory, which promises unprecedented sensitivity and resolution in the detection
of cosmic gamma-ray sources in the ∼ 30 GeV to ∼ 100 TeV energy range. As
dark sub-halos are expected to appear as unidentified (point) sources in the CTAO
GPS data, we employ a machine learning (ML)-based approach, the AutoSour-
ceID framework, leveraging U-shaped networks (U-Nets) and Laplacian of Gaus-
sian (LoG) filter, for automatic source detection and localization, and apply it to
simulated GPS data. We establish detection thresholds for U-Nets trained on dif-
ferently scaled counts (counts, square root or log of counts) and identify which
approach offers best results (in terms of flux sensitivity and location accuracy).
Our findings suggest that using log-scaled counts yields a factor of 1.7 lower flux
threshold compared to counts alone. In addition, we compare our ML outcomes
with traditional methods; however, this comparison is not straightforward, as ML
and traditional approaches fundamentally differ in their methodologies and un-
derlying assumptions. Nevertheless, The flux threshold obtained using log-scaled
counts is comparable to that of the traditional likelihood-based detection method
implemented in the Gammapy library, although further study is needed to estab-
lish a more definitive comparison. These preliminary results also suggest that the
flux threshold for detecting 90% of true sources with the ML approach is approx-
imately two times lower than the sensitivity reported for the GPS in the CTAO
publication. Although these results are not directly comparable due to differences
in methodology, they hint that ML methods may offer superior performance in
certain scenarios. Furthermore, we discuss the implications of our results on the
sensitivity to DM sub-halos, improving it by a factor of 4, highlighting the possi-
bility of detecting at least one sub-halo with a cross section approximately ⟨σv⟩ =
2.4 × 10−23 cm3 /s.
Keywords: Cherenkov Telescope Array Observatory, dark matter, sub-halos, machine learning, gamma-rays, master's thesis
Published in RUNG: 06.09.2024; Views: 1322; Downloads: 19
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5. Empirical observations on the interpretation of the Macedonian articles : master's thesisMetodi Efremov, 2024, master's thesis Abstract: This thesis investigates the use and the interpretation of three alleged definite articles in Macedonian from a formal perspective. It is concerned with the following questions: (i) does Macedonian indeed have a definite article? (ii) are all three articles in Macedonian definite articles or demonstratives? (iii) what are the formal features that distinguish among these items and how are they licensed in different semantic contexts? The thesis provides evidence that Macedonian has only one definite article – the t-root one – as it presupposes uniqueness and does not have a deictic feature. The other two items – the v- and n-root articles – are at the intersection of a definite article and a demonstrative: they have a deictic feature but do not presuppose uniqueness or non-uniqueness. In addition, it is demonstrated that Macedonian has a set of three demonstratives that have a deictic feature and presuppose non-uniqueness.
Keywords: master's thesis, semantics, definite articles, demonstrative, uniqueness, deixis, reference
Published in RUNG: 12.07.2024; Views: 1826; Downloads: 39
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10. Chaos, commons, and relocating the spectral classroom : Cha-os, com-mons, and relo cating the spectral classroom: masters thesisOwen Moran, 2023, master's thesis Keywords: chaos, commons, education, chaosmosis, enclosures, enlivenment, adtech, digital milieu, spectral classroom, master's thesis
Published in RUNG: 21.02.2023; Views: 3118; Downloads: 0
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