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Numerical and experimental methods for the assessment of a human finger-inspired soft pneumatic actuator for gripping applications.
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June 2025
Department of Artificial Intelligence and Machine Learning, Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Lavale, Pune, Maharashtra, India.
The increasing demand for soft robotic systems in agricultural, biomedical and other applications has driven the development of actuators that can mimic the flexibility and adaptability of human muscles. Several studies have explored the design and implementation of soft actuators for robotic applications, however, there is a need for soft actuators demonstrating delicate gripping capabilities but also excel in specific biomedical applications, such as therapeutic massaging. The objective of this work is to develop a multi-finger soft pneumatic actuator mimicking human fingers for Ayurvedic therapeutic massaging and gripping applications.
View Article and Find Full Text PDFSpecies identification for Indian seafood markets: A machine learning approach with a fish dataset.
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School of CSIT, Symbiosis Skills and Professional University, Kiwale, Pune, India.
The Indian sea fish market is a dynamic and significant sector, contributing to both the domestic economy and the global seafood trade. This fish dataset is specifically curated for machine learning applications in the Indian seafood industry. It includes a comprehensive collection of images representing eight commercially significant fish species native to Indian waters, comprising a total of 8488 images.
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John von Neumann Faculty of Informatics, Obuda University, Budapest, Hungary.
Global adoption of wind energy continues to increase, while improving the efficiency of turbine settings requires reliable wind speed (WS) models. The latest models rely on artificial intelligence (AI) optimizations which constructs tests on a range of novel hybrid models to examine the reliability. Gradient Boosting (GB), Random Forest (RF), and Long Short-Term Memory (LSTM) are used in new combinations for data pre-processing.
View Article and Find Full Text PDFUse of Artificial Intelligence in Lower Gastrointestinal and Small Bowel Disorders: An Update Beyond Polyp Detection.
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Machine learning and its specialized forms, such as Artificial Neural Networks and Convolutional Neural Networks, are increasingly being used for detecting and managing gastrointestinal conditions. Recent advancements involve using Artificial Neural Network models to enhance predictive accuracy for severe lower gastrointestinal (LGI) bleeding outcomes, including the need for surgery. To this end, artificial intelligence (AI)-guided predictive models have shown promise in improving management outcomes.
View Article and Find Full Text PDFArtificial intelligence-based cardiovascular/stroke risk stratification in women affected by autoimmune disorders: a narrative survey.
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Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, 95661, USA.
Women are disproportionately affected by chronic autoimmune diseases (AD) like systemic lupus erythematosus (SLE), scleroderma, rheumatoid arthritis (RA), and Sjögren's syndrome. Traditional evaluations often underestimate the associated cardiovascular disease (CVD) and stroke risk in women having AD. Vitamin D deficiency increases susceptibility to these conditions.
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