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Enhanced particle swarm optimization with chaotic search for offshore micro-energy systems.
Sci Rep
January 2025
School of Information Engineering, Hunan University of Science and Engineering, Yonzhou, 425199, Hunan, China.
As the global energy landscape shifts and sustainability becomes crucial, the offshore oil and gas sector confronts significant challenges and opportunities. This paper addresses the issues of energy efficiency and environmental impact of optimizing offshore micro-energy systems (OMIES) by proposing a multi-objective optimization model that integrates chaotic local search and particle swarm optimization (PSO). The model aims to achieve optimal scheduling of the energy system by comprehensively considering operational costs, carbon emissions, energy utilization efficiency, and energy fluctuation risks.
View Article and Find Full Text PDFEfficacy of home based computerized adaptive cognitive training in patients with post stroke cognitive impairment: a randomized controlled trial.
Sci Rep
January 2025
Department of Psychology, Government MLB Girls PG College, Kila Bhawan, Indore, Madhya Pradesh, India.
Post-stroke cognitive impairment is a common consequence of stroke, characterized by deficits in language, cognitive functioning, functional abilities. Innovative technological approaches, such as computerized cognitive retraining, offer promising strategies for mitigating the cognitive challenges. Despite their potential, the impact of these interventions on neuropsychological function and daily living capabilities has poor outcomes.
View Article and Find Full Text PDFMeasuring Precipitation via Microwave Bands with a High-Accuracy Setup.
Sensors (Basel)
December 2024
Department of Informatics and Telecommunications, University of Peloponnese, Acadimaikou G.K. Vlachou, 22100 Tripolis, Greece.
The urgent need for timely and accurate precipitation estimations in the face of ongoing climate change and the increasing frequency and/or intensity of extreme weather events underscores the necessity for innovative approaches. Recently, several studies have focused on estimating the precipitation rate through induced attenuation of radio frequency (RF) signals, which are abundant in modern communication systems. Most research has concentrated on frequencies exceeding 10 GHz, as attenuation at lower frequencies is minimal, posing measurement challenges.
View Article and Find Full Text PDFInvestigation of Separating Temperature-Induced Structural Strain Using Improved Blind Source Separation (BSS) Technique.
Sensors (Basel)
December 2024
The State Key Laboratory for the Safety, Long-Life, Health Operation and Maintenance of Long-Span Bridges, Jiangsu Provincial Institute of Traffic Science (JSTI Group), Nanjing 210098, China.
The strain data acquired from structural health monitoring (SHM) systems of large-span bridges are often contaminated by a mixture of temperature-induced and vehicle-induced strain components, thereby complicating the assessment of bridge health. Existing approaches for isolating temperature-induced strains predominantly rely on statistical temperature-strain models, which can be significantly influenced by arbitrarily chosen parameters, thereby undermining the accuracy of the results. Additionally, signal processing techniques, including empirical mode decomposition (EMD) and others, frequently yield unstable outcomes when confronted with nonlinear strain signals.
View Article and Find Full Text PDFMachine Learning Techniques for Sensor-Based Human Activity Recognition with Data Heterogeneity-A Review.
Sensors (Basel)
December 2024
Department of Electrical, Computer, and Software Engineering, The University of Auckland, Auckland 1010, New Zealand.
Sensor-based Human Activity Recognition (HAR) is crucial in ubiquitous computing, analyzing behaviors through multi-dimensional observations. Despite research progress, HAR confronts challenges, particularly in data distribution assumptions. Most studies assume uniform data distributions across datasets, contrasting with the varied nature of practical sensor data in human activities.
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