Search

We present the observations of a quiescent filament eruption and its deflection from the radial direction. The event occurred in the southern solar hemisphere on 2021 May 9 and was observed by the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO), by the STEREO A Observatory and GONG. Part of the filament erupted in the west direction, while major part of the filament deviated towards east direction. LASCO observed a very weak CME towards the west direction where it faded quickly. Moreover, the eruption was associated with CME observed by STEREO A COR1 and COR2. Our observations provide the evidence that the filament eruption was highly non-radial in nature., Comment: Accepted in the Proceedings of IAUS 388

A virtual embodiment can benefit conversational agents, but it is unclear how their personalities and non-verbal behavior influence the User Experience and Social Presence in Augmented Reality (AR). We asked 30 users to converse with a virtual assistant who gives recommendations about city activities. The participants interacted with two different personalities: Sammy, a cheerful blue mouse, and Olive, a serious green human-like agent. Each was presented with two body languages - happy/friendly and annoyed/unfriendly. We conclude how agent representation and humor affect User Experience aspects, and that body language is significant in the evaluation and perception of the AR agent.

Web tables contain a large amount of valuable knowledge and have inspired tabular language models aimed at tackling table interpretation (TI) tasks. In this paper, we analyse a widely used benchmark dataset for evaluation of TI tasks, particularly focusing on the entity linking task. Our analysis reveals that this dataset is overly simplified, potentially reducing its effectiveness for thorough evaluation and failing to accurately represent tables as they appear in the real-world. To overcome this drawback, we construct and annotate a new more challenging dataset. In addition to introducing the new dataset, we also introduce a novel problem aimed at addressing the entity linking task: named entity recognition within cells. Finally, we propose a prompting framework for evaluating the newly developed large language models (LLMs) on this novel TI task. We conduct experiments on prompting LLMs under various settings, where we use both random and similarity-based selection to choose the examples presented to the models. Our ablation study helps us gain insights into the impact of the few-shot examples. Additionally, we perform qualitative analysis to gain insights into the challenges encountered by the models and to understand the limitations of the proposed dataset.

The capabilities of large language models (LLMs) have been successfully applied in the context of table representation learning. The recently proposed tabular language models have reported state-of-the-art results across various tasks for table interpretation. However, a closer look into the datasets commonly used for evaluation reveals an entity leakage from the train set into the test set. Motivated by this observation, we explore adversarial attacks that represent a more realistic inference setup. Adversarial attacks on text have been shown to greatly affect the performance of LLMs, but currently, there are no attacks targeting tabular language models. In this paper, we propose an evasive entity-swap attack for the column type annotation (CTA) task. Our CTA attack is the first black-box attack on tables, where we employ a similarity-based sampling strategy to generate adversarial examples. The experimental results show that the proposed attack generates up to a 70% drop in performance., Comment: Accepted at TaDA workshop at VLDB 2023

Despite recent advancements in tabular language model research, real-world applications are still challenging. In industry, there is an abundance of tables found in spreadsheets, but acquisition of substantial amounts of labels is expensive, since only experts can annotate the often highly technical and domain-specific tables. Active learning could potentially reduce labeling costs, however, so far there are no works related to active learning in conjunction with tabular language models. In this paper we investigate different acquisition functions in a real-world industrial tabular language model use case for sub-cell named entity recognition. Our results show that cell-level acquisition functions with built-in diversity can significantly reduce the labeling effort, while enforced table diversity is detrimental. We further see open fundamental questions concerning computational efficiency and the perspective of human annotators., Comment: 8 pages

Specialized transformer-based models for encoding tabular data have gained interest in academia. Although tabular data is omnipresent in industry, applications of table transformers are still missing. In this paper, we study how these models can be applied to an industrial Named Entity Recognition (NER) problem where the entities are mentioned in tabular-structured spreadsheets. The highly technical nature of spreadsheets as well as the lack of labeled data present major challenges for fine-tuning transformer-based models. Therefore, we develop a dedicated table data augmentation strategy based on available domain-specific knowledge graphs. We show that this boosts performance in our low-resource scenario considerably. Further, we investigate the benefits of tabular structure as inductive bias compared to tables as linearized sequences. Our experiments confirm that a table transformer outperforms other baselines and that its tabular inductive bias is vital for convergence of transformer-based models., Comment: EMNLP 2022 Industry Track

We present the observations of three sympathetic filament eruptions occurring on 19 July 2015 namely F1, F2, and F3. The events were observed in UV/EUV wavelengths by Atmospheric Imaging Assembly onboard the Solar Dynamics Observatory and by Global Oscillation Network Group telescope in H{\alpha} line. As filament F1 starts to erupt, a part of it falls close to the location of the F2 and F3 filaments. This causes the eruption of F2 and F3 during which the two filaments merge together and trigger a medium-class CME and a long-duration GOES C2.1 class flare. We discuss the dynamics and kinematics of these three filament eruptions and related phenomena., Comment: 19 pages, 12 Figures

High-quality Web tables are rich sources of information that can be used to populate Knowledge Graphs (KG). The focus of this paper is an evaluation of methods for table-to-class annotation, which is a sub-task of Table Interpretation (TI). We provide a formal definition for table classification as a machine learning task. We propose an experimental setup and we evaluate 5 fundamentally different approaches to find the best method for generating vector table representations. Our findings indicate that although transfer learning methods achieve high F1 score on the table classification task, dedicated table encoding models are a promising direction as they appear to capture richer semantics., Comment: Accepted at DL4KF@ISWC

One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web" and described in its report is that of a: "Public FAIR Knowledge Graph of Everything: We increasingly see the creation of knowledge graphs that capture information about the entirety of a class of entities. [...] This grand challenge extends this further by asking if we can create a knowledge graph of "everything" ranging from common sense concepts to location based entities. This knowledge graph should be "open to the public" in a FAIR manner democratizing this mass amount of knowledge." Although linked open data (LOD) is one knowledge graph, it is the closest realisation (and probably the only one) to a public FAIR Knowledge Graph (KG) of everything. Surely, LOD provides a unique testbed for experimenting and evaluating research hypotheses on open and FAIR KG. One of the most neglected FAIR issues about KGs is their ongoing evolution and long term preservation. We want to investigate this problem, that is to understand what preserving and supporting the evolution of KGs means and how these problems can be addressed. Clearly, the problem can be approached from different perspectives and may require the development of different approaches, including new theories, ontologies, metrics, strategies, procedures, etc. This document reports a collaborative effort performed by 9 teams of students, each guided by a senior researcher as their mentor, attending the International Semantic Web Research School (ISWS 2019). Each team provides a different perspective to the problem of knowledge graph evolution substantiated by a set of research questions as the main subject of their investigation. In addition, they provide their working definition for KG preservation and evolution.

A single case study of a CBP in an equatorial coronal hole with an exceptionally large size is investigated to extend our understanding of the formation of mini-filaments, their destabilisation and the origin of the eruption triggering the formation of jet-like features recorded in the extreme-ultraviolet (EUV) and X-ray emission. We aim to explore the nature of the so-called micro-flares in CBPs associated with jets in coronal holes and mini coronal mass ejections in the quiet Sun. Co-observations from the Atmospheric Imaging Assembly (AIA) and Helioseismic Magnetic Imager (HMI) on board the Solar Dynamics Observatory, and GONG Halpha images are used together with a Non-Linear Force Free Field (NLFFF) relaxation approach, where the latter is based on a time series of HMI line-of-sight magnetograms. A mini-filament (MF) that formed beneath the CBP arcade around 3-4 h before the eruption is seen in the Halpha and EUV AIA images to lift up and erupt triggering the formation of an X-ray jet. No significant photospheric magnetic flux concentration displacement (convergence) is observed and neither is magnetic flux cancellation between the two main magnetic polarities forming the CBP in the time period leading to the MF liftoff. The CBP micro-flare is associated with three flare kernels that formed shortly after the MF liftoff. No observational signature is found for reconnection beneath the erupting MF. The applied NLFFF modelling successfully reproduces both the CBP loop complex as well as the magnetic flux rope that hosts the MF during the build-up to the eruption., Comment: 13 pages, 11 figures, the abstract has been reduced from its original length, accepted by A&A

As the Internet of Things continues to take hold in the commercial world, the teams designing these new technologies are constantly evolving and turning their hand to uncharted territory. This is especially key within the field of secondary service design as businesses attempt to utilize and find value in the sensor data being produced by connected products. This paper discusses the ways in which a commercial design team use smart thermostat data to prototype an advice-giving chatbot. The team collaborate to produce a chat sequence through careful ordering of data & reasoning about customer reactions. The paper contributes important insights into design methods being used in practice within the under researched areas of chatbot prototyping and secondary service design., Comment: Proceedings of the CHI 2019 Workshop on New Directions for the IoT: Automate, Share, Build, and Care, (arXiv:cs/0101200)

The domestic environment is a key area for the design and deployment of autonomous systems. Yet research indicates their adoption is already being hampered by a variety of critical issues including trust, privacy and security. This paper explores how potential users relate to the concept of autonomous systems in the home and elaborates further points of friction. It makes two contributions. One methodological, focusing on the use of provocative utopian and dystopian scenarios of future autonomous systems in the home. These are used to drive an innovative workshop-based approach to breaching experiments, which surfaces the usually tacit and unspoken background expectancies implicated in the organisation of everyday life that have a powerful impact on the acceptability of future and emerging technologies. The other contribution is substantive, produced through participants efforts to repair the incongruity or "reality disjuncture" created by utopian and dystopian visions, and highlights the need to build social as well as computational accountability into autonomous systems, and to enable coordination and control., Comment: Personal and Ubiquitous Computing

We employ a quantum master equations approach based on a vectorial Maxwell-pseudospin model to compute the quantum evolution of the spin populations and coherences in the fundamental singlet trion transition of a negatively charged quantum dot embedded in a micropillar cavity. Excitation of the system is achieved through an ultrashort, either circularly or linearly polarised resonant pulse. By implementing a realistic micropillar cavity geometry, we numerically demonstrate a giant optical phase shift ($\sim \pm \pi/2$) of a resonant circularly polarised pulse in the weak-coupling regime. The phase shift that we predict considerably exceeds the experimentally observed Kerr rotation angle $(\sim{6 ^{\circ}})$ under a continuous-wave, linearly polarised excitation. By contrast, we show that a linearly polarised pulse is rotated to a much lesser extent of a few degrees. Depending on the initial boundary conditions, this is due to either retardation or advancement in the amplitude build-up in time of the orthogonal electric field component. Unlike previous published work, the dominant spin relaxation and decoherence processes are fully accounted for in the system dynamics. Our dynamical model can be used for optimisation of the optical polarisation rotation angle for realisation of spin-photon entanglement and ultrafast polarisation switching on a chip., Comment: 14 pages, 10 figures

Authoring location-based experiences involving multiple participants, collaborating or competing in both indoor and outdoor mixed realities, is extremely complex and bound to serious technical challenges. In this work, we present the first results of the MAGELLAN European project and how these greatly simplify this creative process using novel authoring, augmented reality (AR) and indoor geolocalisation techniques.

We have developed a model of the nonlinear polariton dynamics in realistic 3D non-planar microcavity wires in the driven-dissipative regime. We find that the typical microcavity optical bistability evolves into multistability upon variation of the model parameters. The origin of the multistability is discussed in detail. We apply linear perturbation analysis to modulational instabilities, and identify conditions for localisation of composite multi-mode polariton solitons in the triggered parametric oscillator regime. Further, we demonstrate stable polariton soliton propagation in tilted and tapered waveguides, and determine maximum tilt angles for which solitons still exist. Additionally, we study soliton amplitude and velocity dependence on the wire width, with a view to engineering quantum photonic devices., Comment: 20 pages, 16 figures