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Is It Really You Who Forgot the Password? When Account Recovery Meets Risk-Based Authentication
(2024)
Selection Performance and Reliability of Eye and Head Gaze Tracking Under Varying Light Conditions
(2024)
A PM2.5 concentration prediction framework with vehicle tracking system: From cause to effect
(2023)
Die Projektverbünde in der Förderlinie FDMScouts.nrw haben am 28.03.2023 die Online-Veranstaltung "#datendienstag: Datenmanagementpläne und Forschungsdatenmanagement in Forschungsanträgen" angeboten. Der Vortrag richtete sich an Forschende und Infrastrukturangehörige – vor allem aus der Forschungsförderung, welche die Antragsstellung begleiten.
Viele Drittmittelgeber erwarten als Teil eines Förderantrags Informationen zum Umgang mit Forschungsdaten. Ein formeller Datenmanagementplan (DMP) wird nur in den seltensten Fällen verlangt. Dennoch ist ein DMP für die Arbeit in einem Forschungsprojekt von Vorteil. Welche Vorteile dies sind und welche Anforderungen Forschende bei der Antragstellung bezüglich des FDMs zu erwarten haben, waren – neben Tipps und Tricks – Gegenstand dieser Veranstaltung.
AI systems pose unknown challenges for designers, policymakers, and users which aggravates the assessment of potential harms and outcomes. Although understanding risks is a requirement for building trust in technology, users are often excluded from legal assessments and explanations of AI hazards. To address this issue we conducted three focus groups with 18 participants in total and discussed the European proposal for a legal framework for AI. Based on this, we aim to build a (conceptual) model that guides policymakers, designers, and researchers in understanding users’ risk perception of AI systems. In this paper, we provide selected examples based on our preliminary results. Moreover, we argue for the benefits of such a perspective.
When dialogues with voice assistants (VAs) fall apart, users often become confused or even frustrated. To address these issues and related privacy concerns, Amazon recently introduced a feature allowing Alexa users to inquire about why it behaved in a certain way. But how do users perceive this new feature? In this paper, we present preliminary results from research conducted as part of a three-year project involving 33 German households. This project utilized interviews, fieldwork, and co-design workshops to identify common unexpected behaviors of VAs, as well as users’ needs and expectations for explanations. Our findings show that, contrary to its intended purpose, the new feature actually exacerbates user confusion and frustration instead of clarifying Alexa's behavior. We argue that such voice interactions should be characterized as explanatory dialogs that account for VA’s unexpected behavior by providing interpretable information and prompting users to take action to improve their current and future interactions.
Smart heating systems are one of the core components of smart homes. A large portion of domestic energy consumption is derived from HVAC (heating, ventilation and air conditioning) systems, making them a relevant topic of the efforts to support an energy transition in private housing. For that reason, the technology has attracted attention both from the academic and the industry communities. User interfaces of smart heating systems have evolved from simple adjusting knobs to advanced data visualization interfaces, that allow for more advanced setting such as time tables and status information. With the advent of AI, we are interested in exploring how the interfaces will be evolving to build the connection between user needs and underlying AI system. Hence, this paper is targeted to provide early design implications towards an AI-based user interface for smart heating systems.
The representation, or encoding, utilized in evolutionary algorithms has a substantial effect on their performance. Examination of the suitability of widely used representations for quality diversity optimization (QD) in robotic domains has yielded inconsistent results regarding the most appropriate encoding method. Given the domain-dependent nature of QD, additional evidence from other domains is necessary. This study compares the impact of several representations, including direct encoding, a dictionary-based representation, parametric encoding, compositional pattern producing networks, and cellular automata, on the generation of voxelized meshes in an architecture setting. The results reveal that some indirect encodings outperform direct encodings and can generate more diverse solution sets, especially when considering full phenotypic diversity. The paper introduces a multi-encoding QD approach that incorporates all evaluated representations in the same archive. Species of encodings compete on the basis of phenotypic features, leading to an approach that demonstrates similar performance to the best single-encoding QD approach. This is noteworthy, as it does not always require the contribution of the best-performing single encoding.
There & Back again: Developing a tool for testing of antimicrobial surfaces for space habitat design
(2023)
TSEM: Temporally-Weighted Spatiotemporal Explainable Neural Network for Multivariate Time Series
(2023)
Ziel der neunten Ausgabe des wissenschaftlichen Workshops "Usable Security und Privacy" auf der Mensch und Computer 2023 ist es, aktuelle Forschungs- und Praxisbeiträge auf diesem Gebiet zu präsentieren und mit den Teilnehmer:innen zu diskutieren. Getreu dem Konferenzmotto "Building Bridges" soll mit dem Workshop ein etabliertes Forum fortgeführt und weiterentwickelt werden, in dem sich Expert:innen, Forscher:innen und Praktiker:innen aus unterschiedlichen Domänen transdisziplinär zum Thema Usable Security und Privacy austauschen können. Das Thema betrifft neben dem Usability- und Security-Engineering unterschiedliche Forschungsgebiete und Berufsfelder, z. B. Informatik, Ingenieurwissenschaften, Mediengestaltung und Psychologie. Der Workshop richtet sich an interessierte Wissenschaftler:innen aus all diesen Bereichen, aber auch ausdrücklich an Vertreter:innen der Wirtschaft, Industrie und öffentlichen Verwaltung.
KPI-EDGAR: A Novel Dataset and Accompanying Metric for Relation Extraction from Financial Documents
(2023)
LiDAR-based Indoor Localization with Optimal Particle Filters using Surface Normal Constraints
(2023)
Forschungsdatenmanagement (FDM) nimmt im Forschungsalltag der Hochschulen für angewandte Wissenschaften (HAW) eine zunehmende größere Rolle ein und stellt an viele Forschende bisher unbekannte Anforderungen. So gilt es ein FAIRes und nachhaltiges Datenmanagement im Sinne des Kodex „Leitlinien zur Sicherung guter wissenschaftlicher Praxis“ der DFG zu betreiben – für sich selbst, für die eigene Forschungsgruppe und für die Forschungsgemeinschaft. In dieser Veranstaltung anlässlich des Tags der Forschungsdaten in NRW am 15.11.2022 wurden die wesentlichen Grundzüge des Forschungsdatenmanagements anhand des Forschungsdatenlebenszyklus nähergebracht und Praxisbeispiele und nützliche Links vorgestellt.
Graph databases employ graph structures such as nodes, attributes and edges to model and store relationships among data. To access this data, graph query languages (GQL) such as Cypher are typically used, which might be difficult to master for end-users. In the context of relational databases, sequence to SQL models, which translate natural language questions to SQL queries, have been proposed. While these Neural Machine Translation (NMT) models increase the accessibility of relational databases, NMT models for graph databases are not yet available mainly due to the lack of suitable parallel training data. In this short paper we sketch an architecture which enables the generation of synthetic training data for the graph query language Cypher.
Technological objects present themselves as necessary, only to become obsolete faster than ever before. This phenomenon has led to a population that experiences a plethora of technological objects and interfaces as they age, which become associated with certain stages of life and disappear thereafter. Noting the expanding body of literature within HCI about appropriation, our work pinpoints an area that needs more attention, “outdated technologies.” In other words, we assert that design practices can profit as much from imaginaries of the future as they can from reassessing artefacts from the past in a critical way. In a two-week fieldwork with 37 HCI students, we gathered an international collection of nostalgic devices from 14 different countries to investigate what memories people still have of older technologies and the ways in which these memories reveal normative and accidental use of technological objects. We found that participants primarily remembered older technologies with positive connotations and shared memories of how they had adapted and appropriated these technologies, rather than normative uses. We refer to this phenomenon as nostalgic reminiscence. In the future, we would like to develop this concept further by discussing how nostalgic reminiscence can be operationalized to stimulate speculative design in the present.
P30 - Das Elektrospinnen von halbleitenden Zinndioxidfasern für die Detektion von Wasserstoff
(2022)
Das Ziel dieser Arbeit ist die Entwicklung von dünnen keramischen Fasern als halbleitendes Sensormaterial zum Nachweis von Wasserstoff, möglichst bei Zimmertemperatur. Die elektrische Leitfähigkeit halbleitender Metalloxide ändert sich durch die Einwirkung von oxidierenden und reduzierenden Gasen auf die Oberfläche des Metalloxids. Dieser Effekt kann zur Messung der Gaskonzentration genutzt werden. Die Reaktion von Zinn(IV)-oxid mit Wasserstoff basiert auf der Reduktion des Zinn(IV)-oxids zum Zinn, wobei die Elektronen des Zinn(IV)-oxids im metallischen Zinn verbleiben und dort im nicht gebundenen Zustand zu einer Leitfähigkeitserhöhung beitragen. Die Reaktion des Wasserstoffes kann sowohl mit den Sauerstoffatomen des Oxids als auch mit adsorbierten Sauerstoffatomen an der Oxidoberfläche stattfinden.[ 6] Da die Reaktionen an der Oberfläche des Oxids stattfinden, sollten Sensoren mit einer großen Oberfläche im Vergleich zu metalloxidischen Bulkmaterialien eine höhere Empfindlichkeit aufweisen. [3] Die Verwendung von Fasern anstelle von Dünn- oder Dickschichten führt dabei zu einer besseren Sensitivität gegenüber Gasen.
Taste is a complex phenomenon that depends on the individual experience and is a matter of collective negotiation and mediation. On the contrary, it is uncommon to include taste and its many facets in everyday design, particularly online shopping for fresh food products. To realize this unused potential, we conducted two Co-Design workshops. Based on the participants’ results in the workshops, we prototyped and evaluated a click-dummy smart-phone app to explore consumers’ needs for digital taste depiction. We found that emphasizing the natural qualities of food products, external reviews, and personalizing features lead to a reflection on the individual taste experience. The self-reflection through our design enables consumers to develop their taste competencies and thus strengthen their autonomy in decision-making. Ultimately, exploring taste as a social experience adds to a broader understanding of taste beyond a sensory phenomenon.
Focus on what matters: improved feature selection techniques for personal thermal comfort modelling
(2022)
Occupants' personal thermal comfort (PTC) is indispensable for their well-being, physical and mental health, and work efficiency. Predicting PTC preferences in a smart home can be a prerequisite to adjusting the indoor temperature for providing a comfortable environment. In this research, we focus on identifying relevant features for predicting PTC preferences. We propose a machine learning-based predictive framework by employing supervised feature selection techniques. We apply two feature selection techniques to select the optimal sets of features to improve the thermal preference prediction performance. The experimental results on a public PTC dataset demonstrated the efficiency of the feature selection techniques that we have applied. In turn, our PTC prediction framework with feature selection techniques achieved state-of-the-art performance in terms of accuracy, Cohen's kappa, and area under the curve (AUC), outperforming conventional methods.
In this paper, modeling of piston and generic type gas compressors for a globally convergent algorithm for solving stationary gas transport problems is carried out. A theoretical analysis of the simulation stability, its practical implementation and verification of convergence on a realistic gas network have been carried out. The relevance of the paper for the topics of the conference is defined by a significance of gas transport networks as an advanced application of simulation and modeling, including the development of novel mathematical and numerical algorithms and methods.
In this paper, an analysis of the error ellipsoid in the space of solutions of stationary gas transport problems is carried out. For this purpose, a Principal Component Analysis of the solution set has been performed. The presence of unstable directions is shown associated with the marginal fulfillment of the resistivity conditions for the equations of compressors and other control elements in gas networks. Practically, the instabilities occur when multiple compressors or regulators try to control pressures or flows in the same part of the network. Such problems can occur, in particular, when the compressors or regulators reach their working limits. Possible ways of resolving instabilities are considered.
For most people, using their body to authenticate their identity is an integral part of daily life. From our fingerprints to our facial features, our physical characteristics store the information that identifies us as "us." This biometric information is becoming increasingly vital to the way we access and use technology. As more and more platform operators struggle with traffic from malicious bots on their servers, the burden of proof is on users, only this time they have to prove their very humanity and there is no court or jury to judge, but an invisible algorithmic system. In this paper, we critique the invisibilization of artificial intelligence policing. We argue that this practice obfuscates the underlying process of biometric verification. As a result, the new "invisible" tests leave no room for the user to question whether the process of questioning is even fair or ethical. We challenge this thesis by offering a juxtaposition with the science fiction imagining of the Turing test in Blade Runner to reevaluate the ethical grounds for reverse Turing tests, and we urge the research community to pursue alternative routes of bot identification that are more transparent and responsive.