This work devises an optimized machine learning approach for human arm pose estimation from a single smart-watch. Our approach results in a distribution of possible wrist and elbow positions, which allows for a measur...
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ISBN:
(纸本)9781665491907
This work devises an optimized machine learning approach for human arm pose estimation from a single smart-watch. Our approach results in a distribution of possible wrist and elbow positions, which allows for a measure of uncertainty and the detection of multiple possible arm posture solutions, i.e., multimodal pose distributions. Combining estimated arm postures with speech recognition, we turn the smartwatch into a ubiquitous, low-cost and versatile robot control interface. We demonstrate in two use-cases that this intuitive control interface enables users to swiftly intervene in robot behavior, to temporarily adjust their goal, or to train completely new control policies by imitation. Extensive experiments show that the approach results in a 40% reduction in prediction error over the current state-of-the-art and achieves a mean error of 2.56 cm for wrist and elbow positions.
3D moving object segmentation (MOS) is vital for autonomous systems, providing essential information for downstream tasks like mapping and localization. However, current MOS methods face challenges due to the limitati...
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ISBN:
(纸本)9798350377712;9798350377705
3D moving object segmentation (MOS) is vital for autonomous systems, providing essential information for downstream tasks like mapping and localization. However, current MOS methods face challenges due to the limitation of existing datasets, which are sparse in moving objects and limited in scene diversity. Meanwhile, the prevalent methods are projection-based, struggling with the challenge of blurred boundaries. To tackle the dataset issue, we introduce a nuScenes-based MOS dataset, which provides richer scenes and more dynamic instances. To alleviate the boundary blurring issue and further improve accuracy and generalizability, we propose a dual-branch multimodal fusion MOS network, MOSFormer. The Transformer structure is incorporated to extract spatio-temporal information better, while image semantic information is utilized to refine the boundaries of moving objects. Finally, experiments on two datasets show that our method achieves state-of-the-art performance, and a mapping experiment with our method confirms its effectiveness in downstream tasks such as mapping and localization.
With the integration of large-scale distributed PV into the distribution network, the PV penetration rate is increasing, and the imbalance between the PV output and the load leads to the reverse current in the line, c...
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作者：
Yamuna, P.V.Sunila, M.S.G.E.C Thrissur
Affiliated to Apj Abdul Kalam Technological University Department of Electrical and Electronics Engineering Kerala India
For a two-area power system, a unique adaptive sliding mode-based load frequency control is suggested in this work. Turbines of the non-reheat type are used in the power system. Despite the presence of external load d...
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Digital filter design plays a crucial role in signal processing applications, aiming to enhance, extract, or suppress specific components of a signal. Soft computing techniques have emerged as effective methods for de...
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In order to improve the collaborative decision-making efficiency of helicopter rescue missions in complex dynamic environments, a three-layer collaborative decision-making mechanism based on intelligentcomputing was ...
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Several industries have found methods of deep learning to be beneficial. One such area is cyber security. In order to monitor and reduce network risks. The classification technique of deep learning is applied to obser...
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The increasing global interest in renewable energy-based power systems is fuelled by their abundance and environmentally friendly characteristics. Hybrid Renewable Energy systems (HRES) represent a novel development, ...
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ISBN:
(纸本)9798350385939;9798350385922
The increasing global interest in renewable energy-based power systems is fuelled by their abundance and environmentally friendly characteristics. Hybrid Renewable Energy systems (HRES) represent a novel development, integrating multiple sustainable sources like wind turbines, solar photovoltaic (PV) systems, and other renewables like ocean, wave, and geothermal energy. Integrating multiple renewable energy sources such as solar, wind, hydro, and biomass and energy storage systems as a backup for the reliable power supply has been considered. To ensure uninterrupted power supply to the growing community and industrial sector, proper synchronization and management of alternative power sources are imperative through an energy management system. The hybrid energy system optimizes power-generating module quantities and sizes, including PV systems, wind turbines, batteries, and diesel generators, while meeting load requirements. Implemented in MATLAB Simulink, alongside a full model of the hybrid renewable energy systems, simulation results illustrate the effectiveness in maintaining voltage and frequency within acceptable ranges during diverse operating conditions. In conclusion, this manuscript offers a comprehensive study on the optimization and control of a solar-wind hybrid renewable energy system, serving as a valuable tool for designing and operating such systems in remote and islanded communities.
The rising need for efficient management of water resources necessitates the inclusion of advanced controlsystems in essential infrastructure, such as water reservoirs. This study suggests a systematic approach that ...
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Intermediate representations (IRs) are fundamental to classical and quantum computing, bridging high-level quantum programming languages and the hardware-specific instructions required for execution. This paper review...
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Intermediate representations (IRs) are fundamental to classical and quantum computing, bridging high-level quantum programming languages and the hardware-specific instructions required for execution. This paper reviews the development of quantum IRs, focusing on their evolution and the need for abstraction layers that facilitate portability and optimization. Monolithic quantum IRs, such as QIR (Lubinski et al. in Front Phys 10:940293, 2022. https://***/10.3389/fphy.2022.940293), QSSA (Peduri et al. in Proceedings of the 31st ACM SIGPLAN internationalconference on compiler construction. CC 2022. Association for computing Machinery, New York, 2022), or Q-MLIR (McCaskey and Nguyen in Proceedings-2021 IEEE internationalconference on Quantum computing and Engineering, QCE, 2021), their effectiveness in handling abstractions, and their hybrid support between quantum-classical operations are evaluated. However, a key limitation is their inability to address qubit locality, an essential feature for distributed quantum computing (DQC). To overcome this, InQuIR (Nishio and Wakizaka in InQuIR: Intermediate Representation for Interconnected Quantum Computers, 2023. https://***/abs/2302.00267) was introduced as an IR specifically designed for distributed systems, providing explicit control over qubit locality and inter-node communication. While effective in managing qubit distribution, InQuIR's dependence on manual manipulation of communication protocols increases complexity for developers. NetQIR (V & aacute;zquez-P & eacute;rez et al. in NetQIR: An Extension of QIR for Distributed Quantum computing, 2024. https://***/abs/2408.03712), an extension of QIR for DQC, emerges as a solution to achieve the abstraction of quantum communications protocols. This review emphasizes the need for further advancements in IRs for distributed quantum systems, which will play a crucial role in the scalability and usability of future quantum networks.
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