Tind Technologies (Norway)
Hes-so: ArODES Open Archive (University of Applied Sciences and Arts Western Switzerland / Haute école spécialisée de Suisse occidentale / FH Westschweiz)Not a member yet
15764 research outputs found
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SSELF ::a specific semiautomated lifecycle footprinting framework to go beyond generic data in LCA
No full textAdvancements in life cycle assessment (LCA) and environmentally extended input–output analysis enable quick generic estimations of the environmental footprint of almost any product and service. However, going beyond a generic estimate to an assessment based on actual, specific supply chain data remains costly and impracticable and demands significant sharing of proprietary data between supply chain actors and the LCA practitioner. Achieving widespread specificity in LCA requires fundamentally changing the way inventory and emission data are collected, stored, and exchanged. This research develops the SSELF (Specific SEmiautomated Lifecycle Footprinting) framework to go beyond generic data in LCA in a way that can scale up, while safeguarding sensitive data. A key feature of the framework is decentralizing inventory collection and footprint calculations. Thus, production functions remain private and upstream impacts are calculated using an iterative approach with a database of unique product identifiers and the footprints reported by other users, capturing changes in the footprints of suppliers. Although this substantially reduces the effort of footprint assessments, implementing the framework in practice presents new challenges, which are identified and discussed in this paper along with recommendations on how they can be addressed and their implications. This work provides important insight into how to get to a point where every product and service has its unique footprint. Broad access to footprints with more specificity is necessary to help consumers reduce their consumption-based impacts and make companies take accountability for, and reduce, their indirect impacts
Stabilizing large-scale electric power grids with adaptive inertia
No full textThe stability of ac power grids relies on ancillary services that mitigate frequency fluctuations. The electromechanical inertia of large synchronous generators is currently the only resource to absorb frequency disturbances on subsecond time scales. Replacing standard thermal power plants with inertialess new renewable sources of energy (NREs) therefore jeopardizes grid stability against, e.g., sudden power-generation losses. To guarantee system stability and compensate the lack of electromechanical inertia in grids with large penetrations of NREs, virtual synchronous generators, which emulate conventional generators, have been proposed. Here, we propose a novel control scheme for virtual synchronous generators, where the provided inertia is large at short times—thereby absorbing faults as efficiently as conventional generators—but decreases over a tunable time scale to prevent coherent frequency oscillations from setting in. We evaluate the performance of this adaptive-inertia scheme under sudden power losses in large-scale transmission grids. We find that it systematically outperforms conventional electromechanical inertia and that it is more stable than previously suggested schemes. Numerical simulations show how a quasioptimal geographical distribution of adaptive-inertia devices not only absorbs local faults efficiently but also significantly increases the damping of interarea oscillations. Our results show that the proposed adaptive-inertia control scheme is an excellent solution to strengthen grid stability in future low-inertia power grids with large penetrations of NREs
Advanced image-based methods for 3D semantic segmentation of lidar point clouds in electrical infrastructure applications
No full textThis study explores AI methods for 3D semantic segmentation relying solely on image data. Using a dataset collected over electrical infrastructures in Switzerland, we evaluate and compare four image-based approaches: majority voting of classifications, logit-based aggregation, distance-weighted logits, and a combination of logits, distance weighting, and depth maps. The results demonstrate that image-only methods can achieve competitive performance, closely approaching the state-of-the-art results achieved with point cloud-based models, while offering the advantages of reduced complexity and cost. Nonetheless, these methods depend on precise alignment between images and point clouds, as well as an effective reprojection process from 2D to 3D.Our experiments also reveal a complementarity between image-based and point cloud-based methods, highlighting the potential for future research on multimodal fusion techniques to fully leverage the strengths of both modalities
Automated classification of celiac disease in histopathological images ::a multi-scale approach
No full textWith a prevalence of 1-2% Celiac Disease (CD) is one of the most commonly known genetic and autoimmune diseases, which is induced by the intake of gluten in genetically predisposed persons. Diagnosing CD involves the analysis of duodenum biopsies to determine the small intestine condition. In this study, we propose a singlescale pipeline and the combination of two single-scale pipelines, forming a multi-scale approach, to accurately classify CD signs in histopathology whole slide images with automatically generated labels. The automatic classification of CD signs in histopathological images of these biopsies has not been extensively studied, resulting in the absence of a standardized guidelines or best-practices for this purpose. To fill this gap, we evaluated different magnifications and architectures, including a pre-trained MoCov2 model, for both single- and multiscale approaches. Furthermore, for the multi-scale approach, methods for aggregating feature vectors from several magnifications are explored. For the single-scale pipeline we achieved an AUC of 0.9975 and a weighted F1-score of 0.9680, while for the multiscale Pipeline an AUC of 0.9966 and a weighted F1-score of 0.9250 was achieved. On large datasets, no significant differences were observed; however, with only 10% of the dataset, the multi-scale framework outperforms the single-scale framework significantly. Moreover, the multi-scale approach requires only half of the dataset and half of the time compared to the best single-scale result to identify the optimal model. In conclusion, the multi-scale framework emerges as an exceptionally efficient solution, capable of delivering superior results with minimal data and resource demands
Puissance et reconnaissance des communs oasiens ::le cas Jemna
No full textL’ethnographie dense et inspirante proposée par M. Kerrou offre l’opportunité de discuter ici deux approches : la théorie de la reconnaissance, qui est au cœur de sa réflexion, et la question des communs qui apparaît particulièrement féconde pour mettre en perspective le processus politique qui sous-tend l’expérience de Jemna
Advancing wound care ::a scoping review protocol on biological parameters in smart dressings
No full textBackground Chronic wounds pose a major healthcare challenge due to delayed healing, infection risks, and they are associated with chronic conditions, such as diabetes and cardiovascular disease. Smart wound dressings, integrating sensor technologies to monitor biological parameters, offer promising advancements in wound management. However, a comprehensive understanding of the parameters they monitor, and their clinical significance remains limited. Aim This protocol outlines a planned scoping review to map the existing literature on biological parameters monitored in smart wound dressings. Methods Following the Joanna Briggs Institute (JBI) methodology and PRISMA-ScR guidelines, a systematic search will be conducted in MEDLINE (via Ovid), Embase, Web of Science, CINAHL (EBSCO), and Google Scholar. The search strategy, developed with librarians, will use controlled vocabulary and keywords. Eligibility criteria will be derived from the Population, Concept, and Context (PCC) framework. Data extraction will be performed using Elicit®, an AI tool, and independently verified. A narrative synthesis will categorise themes. Discussion and conclusions This review will systematically map available evidence, offering insights into key parameters, their relevance in wound management, and gaps in research. Results will guide future studies, healthcare professionals, and policymakers in integrating smart dressings into clinical practice and optimising wound care technologies. Implications for clinical practice This review will support evidence-based decision-making, aiding in the adoption of smart wound dressings to enhance patient care and treatment outcomes
Lightning electromagnetics. Volume 1 ::return stroke modelling and electromagnetic radiation
No full textLightning is important for all scientists and engineers involved with electric installations. It is gaining further relevance since climate warming is causing an increase in lightning strikes, and since the rising numbers of renewable power generators, the electricity grid, and charging infrastructure are susceptible to lightning damage. This is the second edition to this comprehensive work.
Both volumes have been thoroughly revised and updated for this second edition. Volume 1 treats lightning return stroke modelling and lightning electromagnetic radiation, and Volume 2 addresses electrical processes and effects. Chapter coverage includes various models and simulations of lightning strokes, measurements of lightning-generated EM fields, HF, VHF and microwave radiation, and lightning location systems; atmospheric discharge processes, lightning strikes to grounded structures and towers, EM field propagation, interaction with cables, effects on power transmission and distribution systems, effects in the ionosphere, mesosphere and magnetosphere, as well as NOx generation and climate effects. The volumes provide the rules and procedures to combine the readers' understanding with a model of every lightning-related electromagnetic process, and their effects and interactions. Readers obtain first-hand experience through simulations of the EM field of thunderclouds and lightning flashes and their effects.
These volumes are a valuable resource for researchers and engineers in the areas of electrical engineering and physics involved in the fields of electromagnetic compatibility, lightning protection, renewable energy systems, smart grids, and lightning physics, as well as for professionals from telecommunication companies and manufacturers of power equipment, and advanced students
Constipation among women healthcare professionals working at the University Clinics of Kinshasa ::prevalence, habitus, and risk factors
No full textObjective: The aim is to assess the prevalence and clinical characteristics of constipation, as well as the lifestyle habits of women in healthcare professions, to improve the management of this health condition. Patients and Methods: This cross-sectional study was conducted from January 3 to April 3, 2024, among 100 women healthcare professionals working at the University Clinics of Kinshasa. They were women aged 18 years and older, either employed or in training, in apparently good health, and who had given their consent to participate. The questionnaire contained data on sociodemographic and clinical characteristics, lifestyle habits, and two validated scales: the Bristol Scale and the Knowles, Eckersley, and Scott Symptom Scale (KESS). Mann-Whitney U and Chi-squared tests were used for comparisons. Binary logistic regression was used to identify factors influencing constipation. The significance level was set at 5%. Results: The prevalence of constipation was 44% according to the KESS and 43% according to the Bristol scale. Constipated women were more likely to adopt an improper defecation position (p=0.005) and were less likely to have a bowel movement when they felt the urge or at set times (p<0.001). They used institutional toilets less frequently (p<0.001). They drank less water (p < 0.001) and did not engage in physical activity (p = 0.037). In the multivariate analysis, delaying bowel movements when the urge was felt (aOR: 209.6) and an increased daily water intake (aOR: 0.42) were identified as predictive factors of constipation. Conclusion: Constipation was common among these women. They had poor defecatory and dietary habits, which influenced constipation