In recent years, distributed acoustic sensing has garnered significant interest in seismic monitoring due to its sensitivity to low frequencies, continuity of measurement in both time and space and the capacity to pro...
In recent years, distributed acoustic sensing has garnered significant interest in seismic monitoring due to its sensitivity to low frequencies, continuity of measurement in both time and space and the capacity to provide vast amounts of data regarding the conditions of large structures. This study aims to develop a metrological characterization system to evaluate the performance of the distributed acoustic sensing systems to reconstruct the mechanical wavefront and measure its propagation speed in polyurethane foams. The wave propagation speed measured using distributed acoustic sensing is compared with optical fiber Bragg grating sensors and piezoelectric accelerometer, and the difference is less than 1.5%. The results demonstrate that it is possible to reconstruct the mechanical wavefront using both instrumented sensors, thus validating the application of a distributed acoustic sensing system for mechanical wave measurement in polyurethane foams.
Objective: Glucose homeostasis is the only way to manage diabetic progression as all medications used do not cure diabetes. This study was aimed at verifying the feasibility of lowering glucose with non-invasive ultra...
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Multi-channel speech separation has been successfully applied in a complex real-world environment such as the far-field condition. The common solution to deal with the far-field condition is using a multi-channel sign...
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An e-Commerce company has been using an Enterprise Resource Planning (ERP) system for several years, but is still constrained in its implementation, this is reflected in the number of issue/change request tickets subm...
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作者：
Tu, Deng-YaoLin, Peng-ChanChou, Hsin-HungShen, Meng-RuHsieh, Sun-YuanNational Cheng Kung University
Master Degree Program on Artificial Intelligence Tainan City70101 Taiwan National Cheng Kung University
Institute of Medical Informatics Department of Oncology Department of Genomic Medicine National Cheng Kung University Hospital College of Medicine Department of Computer Science and Information Engineering Tainan City70101 Taiwan National Chi Nan University
Department of Computer Science and Information Engineering Nantou County54561 Taiwan National Cheng Kung University
Graduate Institute of Clinical Medicine Department of Obstetrics and Gynecology Department of Pharmacology National Cheng Kung University Hospital College of Medicine Tainan City70101 Taiwan National Cheng Kung University
Institute of Medical Information Institute of Manufacturing Information and Systems Center for Innovative FinTech Business Models International Center for the Scientific Development of Shrimp Aquaculture Department of Computer Science and Information Engineering Tainan City70101 Taiwan
Automatic liver tumor detection from computed tomography (CT) makes clinical examinations more accurate. However, deep learning-based detection algorithms are characterized by high sensitivity and low precision, which...
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The recent proliferation of hyper-realistic deepfake videos has drawn attention to the threat of audio and visual forgeries. Most previous studies on detecting artificial intelligence-generated fake videos only utiliz...
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Ethereum is one of the most popular blockchain platforms with a high number of adoption in the blockchain world today. Ethereum token (ERC-20) can tokenize any real-world object while it is also possible to exchange t...
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The area of oil palm plantations in Indonesia increased by 7% from 14 million ha in 2017 to 15 million ha in 2021. The vast land requires the support of effective and efficient management techniques to maintain sustai...
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Artificial Intelligence Generated Content (AIGC) Services have significant potential in digital content creation. The distinctive abilities of AIGC, such as content generation based on minimal input, hold huge potenti...
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The ability of robots to imitate human learning strategies-rapidly adapting to new tasks without large datasets-has garnered significant attention in meta-learning. Meta-reinforcement learning seeks to enhance robotic...
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ISBN:
(数字)9798331521554
ISBN:
(纸本)9798331521561
The ability of robots to imitate human learning strategies-rapidly adapting to new tasks without large datasets-has garnered significant attention in meta-learning. Meta-reinforcement learning seeks to enhance robotic agent flexibility across diverse tasks and contexts, offering promise where single-task learning often fails. Despite advancements like multi-task diffusion models and task-weighted optimization mechanisms, effectively training tasks with varying complexities simultaneously remains a major challenge. This paper introduces a novel meta-reinforcement learning method that addresses this issue by clustering the training tasks of robotic arms based on semantic and trajectory similarities, while leveraging adaptive learning rates and task-specific weights proposed by the multitask optimization techniques. Our approach, TEAM, emphasizes performance-driven semantic clustering, optimizing based on robotic task similarity, complexity, and convergence objectives. We also integrate fast adaptive and multi-task optimization of the diffusion model to enhance computational efficiency and adaptability. More specifically, we introduce a cluster-specific optimization technique, using specialized parameters for each group to allow more refined task handling. The experimental validation demonstrates the effectiveness of this scalable method in improving performance, adaptability, and efficiency in real-world, heterogeneous robotic tasks, further advancing robotic computing in meta-reinforcement learning.
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