The paper describes few faults that can be present in Photovoltaic modules and presents results related to training and the testing of a mobile application designed for identifying faults in photovoltaic modules based...
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ISBN:
(数字)9798350308563
ISBN:
(纸本)9798350308570
The paper describes few faults that can be present in Photovoltaic modules and presents results related to training and the testing of a mobile application designed for identifying faults in photovoltaic modules based on thermal images. The mobile application was trained and then tested with different individual and multiple faults. The mobile application can identify with high accuracy both the individual and multiple faults if the thermal images are preprocessed before to be uploaded for analysis.
Increasingly stringent throughput requirements in the industry necessitate the need for lightweight design of high-precision motion systems to allow for high accelerations, while still achieving accurate positioning o...
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This paper focuses on the quadratic nonfragile filtering problem for linear non-Gaussian systems under multiplicative noises,multiple missing measurements as well as the dynamic event-triggered transmission *** multip...
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This paper focuses on the quadratic nonfragile filtering problem for linear non-Gaussian systems under multiplicative noises,multiple missing measurements as well as the dynamic event-triggered transmission *** multiple missing measurements are characterized through random variables that obey some given probability distributions,and thresholds of the dynamic event-triggered scheme can be adjusted dynamically via an auxiliary *** attention is concentrated on designing a dynamic event-triggered quadratic nonfragile filter in the well-known minimum-variance *** this end,the original system is first augmented by stacking its state/measurement vectors together with second-order Kronecker powers,thus the original design issue is reformulated as that of the augmented ***,we analyze statistical properties of augmented noises as well as high-order moments of certain random *** the aid of two well-defined matrix difference equations,we not only obtain upper bounds on filtering error covariances,but also minimize those bounds via carefully designing gain ***,an example is presented to explain the effectiveness of this newly established quadratic filtering algorithm.
The ever increasing need for performance results in increasingly rigorous demands on throughput and positioning accuracy of high-precision motion systems, which often suffer from position dependent effects that origin...
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The quantum steering ellipsoid visualizes the set of all qubit states that can be steered by measuring on another correlated qubit in the Bloch picture. Together with local reduced states, it provides a faithful geome...
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The quantum steering ellipsoid visualizes the set of all qubit states that can be steered by measuring on another correlated qubit in the Bloch picture. Together with local reduced states, it provides a faithful geometric characterization of the underlying two-qubit state so that almost all nonclassical state features can be reflected in its geometric properties. Consequently, the various types of quantum ellipsoids with different geometric properties form an ellipsoid zoo, which, in this paper, is experimentally verified via measurements on many polarization-path photonic states. By generating two-qubit states with high fidelity, the corresponding ellipsoids are constructed to certify the presence of entanglement, one-way Einstein-Podolsky-Rosen steering, discord, and steering incompleteness. It is also experimentally verified that the steering ellipsoid can be reconstructed from using the 12 vertices of the icosahedron as measurement directions. Our results aid progress in applying the quantum steering ellipsoid to reveal nonclassical features of the multiqubit system.
Organisms have evolved innate and acquired immune systems to defend against pathogens like coronaviruses. Similarly, power networks, threatened by cyber-attacks, desire cyber-immunity. Inspired by the immunology resea...
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The phase retrieval (PR) problem involves recovering a signal from amplitude-only measurements and has been extensively studied in various physical measurement and signal processing systems. Recently, there has been i...
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ISBN:
(数字)9798331519315
ISBN:
(纸本)9798331519322
The phase retrieval (PR) problem involves recovering a signal from amplitude-only measurements and has been extensively studied in various physical measurement and signal processing systems. Recently, there has been increasing interest in the quantized phase retrieval (QPR) problem, where the observed amplitude is quantized to binary values. The existing studies have focused on the noiseless case. In this paper, we address a robust QPR problem that accounts for both quantization and noise. We formulate the robust QPR problem using maximum-likelihood estimation (MLE), which results in a non-convex and challenging optimization problem due to the complexity of its likelihood function. To obtain a high-quality solution, we develop an expectation-maximization (EM) algorithm combined with the Wirtinger flow, allowing us to convert the problem into a more manageable form at each iteration. Our method is implemented on both randomly generated synthetic data and image reconstruction tasks. The results demonstrate that our approach significantly enhances signal recovery performance under the combined effects of quantization and noise. Additionally, the proposed method exhibits better runtime efficiency compared to existing approaches.
The phase retrieval (PR) problem involves recovering a signal from amplitude-only measurements and has been extensively studied in various physical measurement and signal processing systems. Recently, there has been i...
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As a data-driven approach, multi-agent reinforcement learning (MARL) has made remarkable advances in solving cooperative residential load scheduling problems. In a simplified scenario, centralized training, the most c...
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computer vision algorithms have been utilized for 3-D road imaging and pothole detection for over two ***,there is a lack of systematic survey articles on state-of-the-art(SoTA)computer vision techniques,especially de...
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computer vision algorithms have been utilized for 3-D road imaging and pothole detection for over two ***,there is a lack of systematic survey articles on state-of-the-art(SoTA)computer vision techniques,especially deep learningmodels,developed to tackle these *** article first introduces the sensing systems employed for 2-D and 3-D road data acquisition,including camera(s),laser scanners and Microsoft *** then comprehensively reviews the SoTA computer vision algorithms,including(1)classical 2-D image processing,(2)3-D point cloud modelling and segmentation and(3)machine/deep learning,developed for road pothole *** article also discusses the existing challenges and future development trends of computer vision-based road pothole detection approaches:classical 2-D image processing-based and 3-D point cloud modelling and segmentation-based approaches have already become history;and convolutional neural networks(CNNs)have demonstrated compelling road pothole detection results and are promising to break the bottleneck with future advances in self/un-supervised learning for multi-modal semantic *** believe that this survey can serve as practical guidance for developing the next-generation road condition assessment systems.
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