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Smartphone and ICT Use Among Ukrainian Refugees: Technology Support during War, Flight, and Adaptation in Germany
No full textIn conflict-ridden environments, timely and accurate information is critical for those dealing with the dynamic of events. When individuals have to flee, it becomes evident that refugees frequently rely on information and communication technologies (ICT) for information acquisition, travel coordination, and maintaining connections with related parties. Based on 17 interviews, this research explores how Ukrainian refugees, who sought protection in Germany due to the 2022 Russian full-scale invasion, use ICT before, during, and after their flight. By providing empirical findings, the results show in depth how contextual factors, such as infrastructural instability, privacy concerns and an advanced digitalization, interrelate with user behaviors. Analyzing the multifaceted civilian ICT use in the context of war and flight, this exploratory research contributes to the existing research on HCI in migration contexts and connects to several topics of CSCW. By contrasting case specifics, this work highlights what makes Ukraine a special case in this research area. Furthermore, this paper examines both existing and emerging affordances of ICT in the context of flight, and identifies the crucial role of messenger groups for information gathering in all phases of the flight. Lastly, collaborative dimensions of the identified affordances are discussed
Arms Race or Innovation Race? Geopolitical AI Development
No full textChina, the United States, and the European Union have spoken of a global competition surrounding Artificial Intelligence (AI). There is widespread talk of an ‘AI Arms Race’. But what is the nature of this race? We argue that the arms race metaphor does not capture the dynamics of global competition in the AI sector. Instead, we propose the notion of a ‘geopolitical innovation race’ for technological leadership in a networked global economy. Based on an analysis of government documents, we find that actors (1) are open to both zero-sum or positive-sum approaches in AI development, (2) organise actor networks differently based on national innovation cultures, (3) prioritise economics and status next to security concerns, and (4) are open to how AI should be interpreted. Referring to the competitive race of AI research and development, the three technopoles perpetuate the geopoliticisation of innovation and intertwine security and economic interests
Hidden structures of a global infrastructure: Expansion factors of the subsea data cable network
No full textThe network of subsea data cables (SDC) transmits the majority of international and intercontinental data exchanges. After thirty years of fiber-optic SDC installation across the oceans, almost all coastal and island countries gained access to the only global fixed infrastructure network. Still, there is considerable inequality in the number of available SDC accesses, creating deficits in redundancy for less connected states. Previous research hypothesized multiple factors that influenced the build-up of internet infrastructures but failed to verify these assumptions through inferential statistics. This work highlights the national-level factors that made backbone access provision more – or less – attractive to SDC project decision-makers. Our regression analysis of global country-year data (n = 4916) found that socio-economic (population, GDP), political (state fragility, conflict), and geographic factors (seismic hazard, neighboring territories) significantly influenced the number of active and planned accesses. This work can serve as a foundation for further research leveraging quantitative statistics to unveil hidden structures in the construction of material internet infrastructures and support sustainability in the future allocation of international infrastructure development resources in general
Digitale Gewalt gegen Aktivist:innen: Risiken und mögliche Handlungsmöglichkeiten
No full textSeit den frühen 2010er Jahren, insbesondere während der Proteste in Ägypten und Tunesien, wurde die Rolle von Informations- und Kommunikationstechnologien (IKT) für aktivistische Tätigkeiten immer wichtiger. Dies zeigt sich beispielsweise an der Nutzung sozialer Medien durch Aktivist:innen in Myanmar, die nach dem Militärputsch 2021 internationale Aufmerksamkeit erlangen wollten. IKTs bieten zahlreiche Vorteile wie Kosteneinsparungen, Zugang zu alternativen Informationsquellen und die Demokratisierung politischer Beteiligung. Jedoch sind Aktivist:innen mit vielfältigen Herausforderungen und unterschiedlichen Formen von digitaler Gewalt konfrontiert, darunter Internetabschaltungen, Hassrede und Zensurmaßnahmen. Auch ist ein Anstieg digitaler Überwachung, Propaganda und der Manipulation von Informationen zu verzeichnen. Die zunehmende Verbreitung digitaler Gewalt stellt für Aktivist:innen und soziale Bewegungen ein signifikantes Problem dar, was dazu führt, dass sich immer mehr Aktivist:innen selbst zensieren und sich aus den Online-Räumen zurückziehen
ChartChecker: A User-Centred Approach to Support the Understanding of Misleading Charts
No full textMisinformation through data visualisation is particularly dangerous because charts are often perceived as objective data representations. While past efforts to counter misinformation have focused on text and, to some extent, images and video, developing user-centred strategies to combat misleading charts remains an unresolved challenge. This study presents a conceptual approach through ChartChecker, a browser-plugin that aims to automatically extract line and bar chart data and detect potentially misleading features such as non-linear axis scales. A participatory design approach was used to develop a user-centred interface to provide transparent, comprehensible information about potentially misleading features in charts. Finally, a think-aloud study (N = 15) with ChartChecker revealed overall satisfaction with the tools' user interface, comprehensibility, functionality, and usefulness. The results are discussed in terms of improving user engagement, increasing transparency and optimising tools designed to counter misleading information in charts, leading to overarching design implications for user-centred strategies for the visual domain
Modeling and Monitoring Social Media Dynamics to predict Electricity Demand Peaks
No full textInformation spread on social media can lead to sudden, synchronized actions. If this affects electricity demands, it could result in critical consequences for the power grid. With the rise of social media and fake news and the increasing adoption of power-intensive devices, the risk of misinformation attacks by manipulating consumer behavior becomes more relevant. This paper presents a novel approach for modeling the potential impact of social media dynamics on power systems. We present a conceptual monitoring framework for the real-time detection of critical information propagation and the short-term prediction of electricity demand peaks. Based on a social network graph, a stochastic epidemiological model, the Susceptible-Infectious-Recovered (SIR) model, is employed to simulate the "viral" spread of information. To estimate model parameters from real data, an optimization algorithm is developed. Twitter data of a past disaster event is acquired and used to create a generalized propagation dynamics model, which can then be used to analyze the impact of altered power demands. Specifically, we simulate a demand response attack, where households receive misinformation about reduced electricity prices, encouraging them to activate appliances. The results demonstrate that the synchronized behavior of a minority of affected consumers can lead to sudden increases in the aggregated demand, significantly surpassing usual demand levels. Furthermore, we examine the peak demand for electric vehicle (EV) charging at different adoption rates, showing that the consequences of synchronized behavior are amplified. Our innovative approach opens up new possibilities for power grid nowcasting and enhancing critical infrastructure resilience in a proactive manner, which can avoid load shedding
Polygonizing roof segments from high-resolution aerial images using Yolov8-based edge detection
No full textThis study presents a novel approach for roof detail extraction and vectorization using remote sensing images. Unlike previous geometric-primitive-based methods that rely on the detection of corners, our method focuses on edge detection as the primary mechanism for roof reconstruction, while utilizing geometric relationships to define corners and faces. We adapt the YOLOv8 OBB model, originally designed for rotated object detection, to extract roof edges effectively. Our method demonstrates robustness against noise and occlusion, leading to precise vectorized representations of building roofs. Experiments conducted on the SGA and Melville datasets highlight the method’s effectiveness. At the raster level, our model outperforms the state-of-the-art foundation segmentation model (SAM), achieving a mIoU between 0.85 and 1 for most samples and an ovIoU close to 0.97. At the vector level, evaluation using the Hausdorff distance, PolyS metric, and our raster-vector-metric demonstrates significant improvements after polygonization, with a close approximation to the reference data. The method successfully handles diverse roof structures and refines edge gaps, even on complex roof structures of new, excluded from training datasets. Our findings underscore the potential of this approach to address challenges in automatic roof structure vectorization, supporting various applications such as urban terrain reconstruction
Enhanced piezoelectric properties of KNN-based ceramics by synergistic modulation of phase constitution, grain size and domain configurations
No full textDespite significant advancements in KNN-based piezoelectric ceramics, controlling their grain size remains a challenge, impacting reproducibility of piezoelectric properties. Here, we address this issue by initially inves-
tigating the defect chemistry of a ternary system 0.96 K0.48Na0.52Nb0.96Sb0.04O3-0.04Bi0.5Na0.5ZrO3-ABO3
(KNNS-BNZ-ABO3). The ABO3 dopant not only influences the phase constitution, but also induces different charge compensation mechanisms, affecting the grain size and domain configurations of ceramics. Furthermore, the relationship between the grain size and the piezoelectric properties is investigated. The superior piezoelectric charge coefficient (d33) of 435 pC/N, ultra-high planar mode electromechanical coupling factor (kp) of 0.62 and preferable temperature stability are obtained in KNN-based ceramics with large grain size (~50 μm) and hierarchical domain structures. Finally, we elucidated the intrinsic and extrinsic contribution of the grain size on piezoelectric properties of KNN-based piezoceramics based on Rayleigh analysis. Our work provides an effective
paradigm for the development of lead-free piezoelectric ceramics for industrial applications
Tough times for seasoned equity offerings: performance during the COVID pandemic
No full textThis study analyzes the wealth effects of SEO announcements in the US during the COVID-19 pandemic and its main determinants. We find significantly negative abnormal returns of − 8.6%. This provides persuasive evidence that capital markets reacted particularly negative during this period, reflecting higher degrees of uncertainty. We furthermore find that larger firms experience a better SEO performance and that COVID-19 related biotech & healthcare firms react particularly negative. This effect is more negative the lower the company valuation beforehand
Difference-based Equivalent Static Load Method with adaptive time selection and local stiffness adaption
No full textStructural optimization of crash-related problems usually involves nonlinearities in geometry, material, and contact. The Equivalent Static Load (ESL) method provides a method to solve such problems. It has previously been extended to employ an individual Finite Element model describing the deformed geometry at each considered time step under the name Difference-based Equivalent Static Load (DiESL) method. This paper demonstrates how an appropriate selection of the time steps in each cycle can further improve the convergence behavior of the DiESL method. It is shown that the adaptive selection of time steps leads to better objective values and more reliable convergence to the presumed global optimum. Furthermore, the DiESL extension enables the adaption of path-dependent structural properties of the original nonlinear problem like material stiffness in each linear auxiliary load case. In this paper, an adaption of the Young’s modulus on element level in the linear auxiliary problem corresponding to the local plasticization in the nonlinear dynamic problem is successfully implemented. Here, the test examples indicate that an observable improvement can only be obtained if neither the elements in the elastic nor in the plastic range are dominating the structure’s behavior