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Probabilistic indoor temperature forecasting
No full textNumerous studies have demonstrated that energy demand in the building sector, particularly for heating, ventilation, and air conditioning systems, can be reduced by forecasting future indoor temperatures and applying targeted control strategies. Accurate indoor temperature forecasts depend on understanding random variables such as occupancy and the number of active electrical devices. However, detecting these random influences is challenging, leading existing methods to be overly specific, reliant on expensive sensors, and poorly generalizable across different buildings. Moreover, prevalent point forecasting methods fail to account for the uncertainty surrounding future outcomes. In this paper, we propose that instead of attempting to eliminate naturally occurring random disturbances, it is more effective to incorporate these uncertainties into the modeling process. We introduce a deep learning methodology for probabilistic forecasting that predicts future temperatures as a probability distribution, integrating the inherent randomness of the data without requiring direct measurements. The proposed model is based on normalizing flows with flexible Bernstein polynomials and is compared to a Gaussian baseline. This approach enables the estimation of complex distributions via the maximum likelihood principle, with only mild assumptions on its shape. Due to the lack of high-quality real-world data, we use simulated data from various rooms with differing characteristics and evaluate both models in terms of robustness and flexibility. Our results indicate that our model accurately predicts indoor temperature distributions and generalizes well to different and previously unseen rooms. The dataset and code are published along with this paper, to provide reproducible results and benchmark data to the community
Seagrass as Climate-Smart Insulation for the Tropics
Full text linkSeagrass ecosystems provide essential ecological services and are increasingly recog-nized for their potential as sustainable building insulation. While prior studies have examined seagrass insulation in temperate climates, its suitability for tropical con-struction remains largely unexplored. This study assesses the insulation performance, practical challenges, and adoption barriers of seagrass insulation in tropical climates, using building physics simulations and structured expert interviews, with case studies in Seychelles and Auroville, India. Simulation results indicate that seagrass insulation with its high specific heat capacity effectively reduces overheating risks and demon-strates consistently low mould-growth potential under persistently humid tropical conditions. Despite these technical advantages, expert interviews reveal significant non-technical barriers, including negative public perception, regulatory uncertainties, and logistical complexities. Seychelles faces particular hurdles such as limited coastal storage capacity and stringent environmental regulations. In contrast, Auroville emerges as an ideal demonstration site due to its strong sustainability culture and openness to innovative building materials. The study further identifies that integrating seagrass insulation into a structured, regulated supply chain—from sustainable har-vesting and processing to quality assurance—could simultaneously enhance ecosystem conservation and material availability. Implementing a harvesting framework analo-gous to sustainable forestry could ensure environmental protection alongside supply stability. The findings emphasize the urgent need for targeted awareness initiatives, regulatory alignment, and economic feasibility assessments to overcome barriers and enable wider adoption. Overall, this research highlights seagrass insulation as a prom-ising, climate-positive construction material with strong potential under tropical con-ditions, provided that identified logistical, societal, and regulatory challenges are ad-dressed through dedicated research, stakeholder collaboration, and practical pilot projects
Financing the Future: Overcoming Venture Capital Barriers for Sustainable Startups
No full textSecuring venture capital is a significant challenge for sustainable startups, despite their potential to drive long-term environmental and social benefits. This paper identifies and discusses the main barriers to funding sustainable startups. It explores potential solutions enhancing their access to capital, which ultimately contributes to a more sustainable, innovation-driven economy. Traditional venture capitalists often perceive these startups as higher-risk investments with potentially lower returns. Key concerns include technological uncertainties, exit risks, and political factors. Additionally, while sustainable entrepreneurs emphasize environmental and social aspects in their business plans, these factors play a minor role in traditional investment decisions, leading to misalignment in investor expectations. Proposed solutions include increased government support and funding programs for sustainable startups, along with intermediaries and financially focused business plans to reduce information asymmetries between investors and entrepreneurs. ©2025 IEE
Modellierung, Formfindung und Tragwerksanalyse von Membranbauten
No full textMembrantragwerke ermöglichen durch den Einsatz dünner, ausschließlich zugbeanspruchter Materialien die Realisierung leichter und weitgespannter Flächentragwerke. Aufgrund der großen Auswahl an textilen Werkstoffen ergeben sich vielfältige Anwendungsbereiche, die von kleinen Überdachungen bis zu großflächigen Konstruktionen reichen. Die Formfindung erfolgt mithilfe numerischer Verfahren, bei denen definierte Vorspannzustände in der Membran und Seilen berücksichtigt werden, um eine stabile Gleichgewichtsform zu berechnen. Die Stabilität wird durch Vorspannung sowie doppelt gekrümmte Geometrien gewährleistet. Auf diese formgefundenen Flächen werden alle weiteren Lasten aufgesetzt, wodurch das Tragwerk weiter analysiert werden kann.
Für diese Arbeit werden die Programme RFEM 6 von Dlubal Software sowie SOFiSTiK in Kombination mit Rhino 8, aufgrund ihrer weiten Verbreitung in der Praxis, eingesetzt. Während RFEM 6 eine grafische Benutzeroberfläche bietet, erfolgt die Eingabe in SOFiSTiK textbasiert über den Editor Teddy. Nach Abschluss der Modellierung erfolgt die Suche der optimalen Form durch die iterative Anpassung der Vorspannung. Ziel ist es, eine Geometrie zu finden, die sowohl alle Anforderungen an die Gebrauchstauglichkeit und Tragfähigkeit sowie im Hinblick auf die konstruktive Umsetzung erfüllt
Development of CuTouch: A Fingertip Somatosensory Training System Applying Multimodal Vibrotactile Stimulation
No full textCuTouch is an innovative somatosensory training system aimed at improving diminished discriminative cutaneous sensitivity in the fingertips. The system employs a multimodal approach with visual, audio, and tactile cues, integrating neuroplasticity and spasticity therapy techniques to enhance attention and subsequently sensory perception. The system consists of two core components: the App and the Station. The mobile application facilitates cutaneous stimulation sessions, conducts user testing, and monitors progress. It activates specific points and patterns, simulates textures, and synchronizes vibrotactile feedback with music note onsets and frequencies. The app’s discrimination testing module is inspired by established two-point discrimination and tactile discrimination tests, enabling standardized, remote assessments with consistent pressure. The Station, a specialized hardware device, delivers precise vibrotactile stimulation, offering a comprehensive at-home training solution. Future research will explore expanding the system’s capabilities and applications to confirm its effectiveness and broader impact further
Applying Machine Learning to Diagnose Impulse Control Disorders in Youth: Towards a Scalable Study Design
No full textThe mental health of children and adolescents is susceptible to being adversely influenced by external stressors and events. A particularly notable example is the COVID-19 pandemic, which has profoundly disrupted the lives of billions of children and families and has been associated with an escalation in mental health issues, including depression, anxiety, and stress-related difficulties. As cited by the World Health Organization, there has been a documented 25% increase in the incidence of anxiety and depression. Before the pandemic, German data indicated a considerable prevalence of anxiety (15%) and depressive symptoms (10%), with similar trends observed worldwide. Impulsivity, in addition, is linked to various behavioral problems in childhood and adolescence, potentially resulting in challenges regarding emotional regulation as individuals advance in age.
This protocol seeks to examine the interrelations between stress, sleep, and impulsivity in children and adolescents. Hence, herein, we present a methodological protocol designed to systematically collect data across these domains. The presented method uses mixed longitudinal methods to investigate the relationship between sleep, stress, and impulsivity in children, combining questionnaires, specialist evaluations, and data obtained from mobile sensors and speech analysis aimed at detecting impulsivity-related discourse patterns.
The data obtained will be used to develop a cost-effective approach involving automatic and structured speech analysis, sleep pattern assessment and stress indicators captured by mobile devices. This will aid in the diagnosis of Impulse Control Disorders (ICD) in children and adolescents and provide valuable information for the diagnosis and implementation of the intervention program. Combining psychological expertise with technological innovation, the project will contribute to fundamental research and the development of digital tools to support young people’s mental health
Community Updates to the DLR ThermoFluid Stream Library
No full textSince its inception in 2021, the user base of the DLR ThermoFluid Stream Library has steadily grown. This growth was accompanied by improved or refined models, new additions such as models for static head pressure and also new examples, especially for teaching. This paper summarizes these updates for the reader and reports on the recent developments
Kritik, Bildung, Orientierung
No full textÜber 400 Vorträge zu philosophischen, ethischen, kulturellen und gesellschaftlichen Themen wurden seit 2005 binnen 20 Jahren in den Vortragsreihen des Studium generale der Hochschule Konstanz gehalten.
Konzipiert, organisiert und moderiert wurden die 33 Vortragsreihen von Volker Friedrich. Der Professor für Schreiben und Rhetorik sieht Kritik, Bildung und Orientierung als Werte an, die in einem Studium ihren Platz haben müssen. Seine Mitstreiter und er blicken in diesem Band auf die Vortragsreihen zurück