Jade University of Applied Sciences

Knowledge of the regional distribution of the world’s population is essential for political and social decisions not only but especially for achieving the 17 Sustainable Development Goals (SDGs). Census and other population data at the subnational level are important for this purpose. However, current population data management platforms largely ignore the spatiotemporal nature of census data. Here, we outline the requirements for a spatiotemporal population data management system and present its general architecture, data model and state of implementation. The developed system currently stores population data from approximately 200 countries, nearly 11 million spatial units and around 770 million individual population figures.

Purpose: Despite radiodensity–mechanical-stiffness correlations across several tissue classes, CT remains almost exclusively visual.We characterise Unity-based 3D haptic segmentation correction via a six-degree-of-freedom haptic stylus rendering local Hounsfield density as force. Methods: Piecewise transfer converts trilinear tip Hounsfield units (HU) into six-HU-band stiffness, rendered as lowpass-smoothed proxy elastic penalty force (Kelvin–Voigt; zero damping), making dense tissue hard. Public abdominal-CT evaluation reports loop-rate/latency, force-versus-depth/distinguishability, and clamp effect. Results: Five hardware recordings gave 213–278,Hz median update rates over a native 1,kHz servo. A five-volume CT-probe simulation (32,388 episodes) yielded rendered-force separation of two soft from three firm bands by 20–68,mN, unanimously across volumes (Friedman, volumes as blocks: χ2 = 20.0, p = 5 · 10−4). Firm bands ordered monotonically by density; the densest two differed by 6,mN because the 0.07,N clamp affected 50% of dense-calcified and 91% of bone samples, respectively. Raising the clamp to 0.20,N increased worst firm-pair separation from |d| = 0.78 to 1.54. Conclusion: Direct density-to-force CT rendering is feasible in-silico with interactive soft-versus-firm separation. Band-table firm-tissue stiffnesses are well-separated; conservative clamp—not mapping—limits discrimination. Future work: device telemetry, raised clamp, perceptual validation, and 1,kHz rendering.

Spatio-temporal data of objects are crucial for scientific research and technical analysis in various dynamic applications. Particularly relevant is the measurement of deformations by photogrammetric deformation analyses, which are carried out in a dense and non-intrusive manner. However, the observation of fast-moving phenomena, such as in wind tunnel experiments, is often affected by kinematics and specific experimental circumstances, which can reduce the quality of the results. In addition, acquired sensor data, which provide information about rotational velocities and accelerations, are often not sufficiently integrated into the photogrammetric analysis. This paper presents a generic framework to integrate kinematic information into the photogrammetric deformation analysis. Based on this, we extend object-based image matching to a sub-pixel accurate spatio-temporal matching method, integrating kinematic data as prior knowledge and simultaneously determining unknown (geometric and kinematic) parameters. We applied the approach in wind tunnel tests with a miniaturized wind turbine, where additional kinematic information about the rotation was acquired. The results demonstrate that the new method generates highly accurate and dense information about blade deformation using photogrammetric and kinematic data. The approach is applicable to a variety of dynamic photogrammetric applications.

Die Anwendung von Serious Games in der Prävention, Therapie und Diagnose von Demenz nimmt kontinuierlich zu. Das Format wird auch zur Krankheitsaufklärung und Sensibilisierung genutzt. Im Rahmen eines Forschungsprojekts wird ein Spiel für An- und Zugehörige entwickelt, das Demenzsymptome sowie mögliche Bewältigungsstrategien vermitteln soll. Evaluationen zeigen, dass der Prototyp eine Alltagssituation von Betroffenen erlebbar macht und eine empathische Auseinandersetzung mit Demenz unterstützt.

The digital documentation of heritage architecture, particularly historic wooden roof structures, has gained significant importance in recent years. Heritage Building Information Modelling (HBIM) has emerged as a crucial field that focuses on the digital representation and management of historic buildings. However, modelling heritage structures in accordance with BIM standards poses challenges due to the complex geometries and specialized information inherent with heritage timber structure. This article presents a workflow that illustrates the integration of an automated, AI-supported analysis of wood knottiness to assess unknown strength values of aged heritage timbers within building life cycle management and supporting the BIM framework. For this purpose, an algorithm for automatic wood knottiness estimation has been developed and implemented as a smartphone-based app-prototype, which facilitates efficient data collection, automatic analysis, and seamless integration into the BIM modelling process, while minimizing potential data loss during exchange.