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Collaboration is an important 21st Century skill. Co-located (or face-to-face) collaboration (CC) analytics gained momentum with the advent of sensor technology. Most of these works have used the audio modality to detect the quality of CC. The CC quality can be detected from simple indicators of collaboration such as total speaking time or complex indicators like synchrony in the rise and fall of the average pitch. Most studies in the past focused on “how group members talk” (i.e., spectral, temporal features of audio like pitch) and not “what they talk”. The “what” of the conversations is more overt contrary to the “how” of the conversations. Very few studies studied “what” group members talk about, and these studies were lab based showing a representative overview of specific words as topic clusters instead of analysing the richness of the content of the conversations by understanding the linkage between these words. To overcome this, we made a starting step in this technical paper based on field trials to prototype a tool to move towards automatic collaboration analytics. We designed a technical setup to collect, process and visualize audio data automatically. The data collection took place while a board game was played among the university staff with pre-assigned roles to create awareness of the connection between learning analytics and learning design. We not only did a word-level analysis of the conversations, but also analysed the richness of these conversations by visualizing the strength of the linkage between these words and phrases interactively. In this visualization, we used a network graph to visualize turn taking exchange between different roles along with the word-level and phrase-level analysis. We also used centrality measures to understand the network graph further based on how much words have hold over the network of words and how influential are certain words. Finally, we found that this approach had certain limitations in terms of automation in speaker diarization (i.e., who spoke when) and text data pre-processing. Therefore, we concluded that even though the technical setup was partially automated, it is a way forward to understand the richness of the conversations between different roles and makes a significant step towards automatic collaboration analytics.
People can describe spatial scenes with language and, vice versa, create images based on linguistic descriptions. However, current systems do not even come close to matching the complexity of humans when it comes to reconstructing a scene from a given text. Even the ever-advancing development of better and better Transformer-based models has not been able to achieve this so far. This task, the automatic generation of a 3D scene based on an input text, is called text-to-3D scene generation. The key challenge, and focus of this dissertation, now relate to the following topics:
(a) Analyses of how well current language models understand spatial information, how static embeddings compare, and whether they can be improved by anaphora resolution.
(b) Automated resource generation for context expansion and grounding that can help in the creation of realistic scenes.
(c) Creation of a VR-based text-to-3D scene system that can be used as an annotation and active-learning environment, but can also be easily extended in a modular way with additional features to solve more contexts in the future.
(d) Analyze existing practices and tools for digital and virtual teaching, learning, and collaboration, as well as the conditions and strategies in the context of VR.
In the first part of this work, we could show that static word embeddings do not benefit significantly from pronoun substitution. We explain this result by the loss of contextual information, the reduction in the relative occurrence of rare words, and the absence of pronouns to be substituted. But we were able to we have shown that both static and contextualizing language models appear to encode object knowledge, but require a sophisticated apparatus to retrieve it. The models themselves in combination with the measures differ greatly in terms of the amount of knowledge they allow to extract.
Classifier-based variants perform significantly better than the unsupervised methods from bias research, but this is also due to overfitting. The resources generated for this evaluation are later also an important component of point three.
In the second part, we present AffordanceUPT, a modularization of UPT trained on the HICO-DET dataset, which we have extended with Gibsonien/telic annotations. We then show that AffordanceUPT can effectively make the Gibsonian/telic distinction and that the model learns other correlations in the data to make such distinctions (e.g., the presence of hands in the image) that have important implications for grounding images to language.
The third part first presents a VR project to support spatial annotation respectively IsoSpace. The direct spatial visualization and the immediate interaction with the 3D objects should make the labeling more intuitive and thus easier. The project will later be incorporated as part of the Semantic Scene Builder (SeSB). The project itself in turn relies on the Text2SceneVR presented here for generating spatial hypertext, which in turn is based on the VAnnotatoR. Finally, we introduce Semantic Scene Builder (SeSB), a VR-based text-to-3D scene framework using Semantic Annotation Framework (SemAF) as a scheme for annotating semantic relations. It integrates a wide range of tools and resources by utilizing SemAF and UIMA as a unified data structure to generate 3D scenes from textual descriptions and also supports annotations. When evaluating SeSB against another state-of-the-art tool, it was found that our approach not only performed better, but also allowed us to model a wider variety of scenes. The final part reviews existing practices and tools for digital and virtual teaching, learning, and collaboration, as well as the conditions and strategies needed to make the most of technological opportunities in the future.
Die vorliegende Arbeit beschäftigt sich mit dem Thema Stemmatologie, d.h. primär der Rekonstruktion der Kopiergeschichte handschriftlich fixierter Dokumente. Zentrales Objekt der Stemmatologie ist das Stemma, eine visuelle Darstellung der Kopiergeschichte, welche i.d.R. graphtheoretisch als Baum bzw. gerichteter azyklischer Graph vorliegt, wobei die Knoten Textzeugen (d.s. die Textvarianten) darstellen während die Kanten für einzelne Kopierprozesse stehen. Im Mittelpunkt des Wissenschaftszweiges steht die Frage des Autorenoriginals (falls ein einziges solches existiert haben sollte) und die Frage der Rekonstruktion seines Textes. Das Stemma selbst ist ein Mittel zu diesem Hauptzweck (Cameron 1987). Der durch für manuelle Kopierprozesse kennzeichnende Abweichungen zunehmend abgewandelte Originaltext ist meist nicht direkt überliefert. Ziel der Arbeit ist es, die semi-automatische Stemmatologie umfassend zu beschreiben und durch Tools und analytische Verfahren weiterzuentwickeln. Der erste Teil der Arbeit beschreibt die Geschichte der computer-assistierten Stemmatologie inkl. ihrer klassischen Vorläufer und mündet in der Vorstellung eines einfachen Tools zur dynamischen graphischen Darstellung von Stemmata. Ein Exkurs zum philologischen Leitphänomen Lectio difficilior erörtert dessen mögliche psycholinguistische Ursachen im schnelleren lexikalischen Zugriff auf hochfrequente Lexeme. Im zweiten Teil wird daraufhin die existenziellste aller stemmatologischen Debatten, initiiert durch Joseph Bédier, mit mathematischen Argumenten auf Basis eines von Paul Maas 1937 vorgeschlagenen stemmatischen Models beleuchtet. Des Weiteren simuliert der Autor in diesem Kapitel Stemmata, um den potenziellen Einfluss der Distribution an Kopierhäufigkeiten pro Manuskript abzuschätzen.
Im nächsten Teil stellt der Autor ein eigens erstelltes Korpus in persischer Sprache vor, welches ebenso wie 3 der bekannten artifiziellen Korpora (Parzival, Notre Besoin, Heinrichi) qualitativ untersucht wird. Schließlich wird mit der Multi Modal Distance eine Methode zur Stemmagenerierung angewandt, welche auf externen Daten psycholinguistisch determinierter Buchstabenverwechslungswahrscheinlichkeiten beruht. Im letzten Teil arbeitet der Autor mit minimalen Spannbäumen zur Stemmaerzeugung, wobei eine vergleichende Studie zu 4 Methoden der Distanzmatrixgenerierung mit 4 Methoden zur Stemmaerzeugung durchgeführt, evaluiert und diskutiert wird.
The 𝒮-cone provides a common framework for cones of polynomials or exponen- tial sums which establish non-negativity upon the arithmetic-geometric inequality, in particular for sums of non-negative circuit polynomials (SONC) or sums of arithmetic- geometric exponentials (SAGE). In this paper, we study the S-cone and its dual from the viewpoint of second-order representability. Extending results of Averkov and of Wang and Magron on the primal SONC cone, we provide explicit generalized second- order descriptions for rational S-cones and their duals.
The sketch map tool facilitates the assessment of OpenStreetMap data for participatory mapping
(2021)
Klonner, Carolin ; Hartmann, Maximilian ; Dischl, Rebecca ; Djami, Lily ; Anderson, Liana ; Raifer, Martin ; Lima-Silva, Fernanda ; Castro Degrossi, Lívia ; Zipf, Alexander ; Albuquerque, João Porto de
A worldwide increase in the number of people and areas affected by disasters has led to more and more approaches that focus on the integration of local knowledge into disaster risk reduction processes. The research at hand shows a method for formalizing this local knowledge via sketch maps in the context of flooding. The Sketch Map Tool enables not only the visualization of this local knowledge and analyses of OpenStreetMap data quality but also the communication of the results of these analyses in an understandable way. Since the tool will be open-source and several analyses are made automatically, the tool also offers a method for local governments in areas where historic data or financial means for flood mitigation are limited. Example analyses for two cities in Brazil show the functionalities of the tool and allow the evaluation of its applicability. Results depict that the fitness-for-purpose analysis of the OpenStreetMap data reveals promising results to identify whether the sketch map approach can be used in a certain area or if citizens might have problems with marking their flood experiences. In this way, an intrinsic quality analysis is incorporated into a participatory mapping approach. Additionally, different paper formats offered for printing enable not only individual mapping but also group mapping. Future work will focus on advancing the automation of all steps of the tool to allow members of local governments without specific technical knowledge to apply the Sketch Map Tool for their own study areas.
The $p$-adic section conjecture predicts that for a smooth, proper, hyperbolic curve $X$ over a $p$-adic field $k$, every section of the map of étale fundamental groups $\pi_1(X) \to G_k$ is induced by a unique $k$-rational point of $X$. While this conjecture is still open, the birational variant in which $X$ is replaced by its generic point is known due to Koenigsmann. Generalising an alternative proof of Pop, we extend this result to certain localisations of $X$ at a set of closed points $S$, an intermediate version in between the full section conjecture and its birational variant. As one application, we prove the section conjecture for $X_S$ whenever $S$ is a countable set of closed points.
For an abeloid variety A over a complete algebraically closed field extension K of Qp, we construct a p-adic Corlette–Simpson correspondence, namely an equivalence between finite-dimensional continuous K-linear representations of the Tate module and a certain subcategory of the Higgs bundles on A. To do so, our central object of study is the category of vector bundles for the v-topology on the diamond associated to A. We prove that any pro-finite-étale v-vector bundle can be built from pro-finite-étale v-line bundles and unipotent v-bundles. To describe the latter, we extend the theory of universal vector extensions to the v-topology and use this to generalise a result of Brion by relating unipotent v-bundles on abeloids to representations of vector groups.
Achlioptas, Dimitris ; Coja-Oghlan, Amin ; Hahn-Klimroth, Maximilian Grischa ; Lee, Joon ; Müller, Noëla ; Penschuck, Manuel ; Zhou, Guangyan
We show that throughout the satisfiable phase the normalized number of satisfying assignments of a random 2-SAT formula converges in probability to an expression predicted by the cavity method from statistical physics. The proof is based on showing that the Belief Propagation algorithm renders the correct marginal probability that a variable is set to “true” under a uniformly random satisfying assignment.
The present paper is concerned with the half-space Dirichlet problem [...] where ℝ𝑁+:={𝑥∈ℝ𝑁:𝑥𝑁>0} for some 𝑁≥1 and 𝑝>1, 𝑐>0 are constants. We analyse the existence, non-existence and multiplicity of bounded positive solutions to (𝑃𝑐). We prove that the existence and multiplicity of bounded positive solutions to (𝑃𝑐) depend in a striking way on the value of 𝑐>0 and also on the dimension N. We find an explicit number 𝑐𝑝∈(1,𝑒√), depending only on p, which determines the threshold between existence and non-existence. In particular, in dimensions 𝑁≥2, we prove that, for 0<𝑐<𝑐𝑝, problem (𝑃𝑐) admits infinitely many bounded positive solutions, whereas, for 𝑐>𝑐𝑝, there are no bounded positive solutions to (𝑃𝑐).