The paper presents automating a clamping mechanism for a vacuum magnetron sputtering equipment and integrating it in the existing pneumatic control system. The clamping mechanism is a vital part of the whole magnetron...
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作者：
Jiao, QingLi, YushanHe, JianpingShanghai Jiao Tong University
Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Dept. of Automation Shanghai China
A growing number of works have investigated inferring the topology of networked dynamical systems from observations, such as to better understand the system behaviour. Despite the tremendous advances, most of them req...
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Automatic seizure prediction is helpful to Epilepsy patients to identify the possibility of seizure events momentarily. This could mitigate the risk faced by them while driving, climbing a staircase, or in similar sit...
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This research introduces an innovative method for forecasting cardiomegaly, a common heart condition marked by an enlarged heart, by combining deep learning and machine learning methods. Using the ResNet50 architectur...
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The paper focuses on monitoring the cardiovascular system using photoplethysmography imaging. This technique allows the detection of slow and fast changes in skin blood perfusion. Based on the knowledge of previous st...
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Power systems are critical infrastructures that require robust monitoring and control mechanisms to ensure reliability, stability, and efficiency. It utilizes the data from Phasor Measurement Units (PMUs) and other mo...
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ISBN:
(数字)9798331519568
ISBN:
(纸本)9798331519575
Power systems are critical infrastructures that require robust monitoring and control mechanisms to ensure reliability, stability, and efficiency. It utilizes the data from Phasor Measurement Units (PMUs) and other monitoring devices, which are sent over communication links. Hence, they are subjected to cyber attacks leading to missing or corrupted values. This can cause unreliable operation of the power system. To address the issue, this paper proposes a modified Time-Series Mixer model to accurately predict multivariate measurements under continuous unavailability of data. The proposed model utilizes the time-mixing and feature-mixing layers, which help to capture temporal and spatial correlation to predict the measurements. Further, it can be utilized in real-time applications in case of attack on any communication channel/PMU measurements, as the single model predicts all the PMU measurements. The performance of the proposed model is validated using data generated for the IEEE 14 bus system via RTDS. Numerical results validate the effectiveness of the proposed method, as the errors are significantly smaller than those obtained by the LSTM model-based consecutive PMU measurement prediction technique.
It is challenging to estimate the limits of DG integration in distribution networks because of the intermittent nature of the type, size, and location of DGs. Furthermore, the premise that the system is balanced is in...
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Because of the likelihood of data breaches and the potential hazards of patient information, healthcare institutions face significant challenges in implementing cloud-based Electronic Health Record (EHR) systems. Curr...
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This study introduces a comprehensive suite of algorithms tailored for advancing Wire Arc Additive Manufacturing (WAAM) processes. The suite includes the Adaptive Deposition Control Algorithm (ADCA), Thermal Feedback ...
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According to China's grid connection standard, the access of doubly-fed wind turbines of small and medium capacity causes the topology and operation mode of the distribution network, and the complexity and variabi...
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