At present, various target detection algorithms are used in detection and classification. It is a problem to improve the accuracy and speed of target detection by using deep learning and neural network model to train ...
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This paper studies the distributed bandit convex optimization problem with time-varying inequality constraints, where the goal is to minimize network regret and cumulative constraint violation. To calculate network cu...
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The present paper considers the model-based and data-driven control of unknown linear time-invariant discretetime systems under event-triggering and self-triggering transmission schemes. To this end, we begin by prese...
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Accurately predicting the Remaining Useful Life (RUL) of integrated circuits in multi-failure modes is critical for ensuring the safe and efficient operation of electronic devices. In this paper, we propose a novel RU...
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Accurately predicting the Remaining Useful Life (RUL) of integrated circuits in multi-failure modes is critical for ensuring the safe and efficient operation of electronic devices. In this paper, we propose a novel RUL prediction method that combines a locally weighted regression method, a Transformer deep neural network, and a multi-failure modes weighted collaborative prediction approach. We first use a locally weighted regression method to eliminate noise from the original feature time series. Then, the feature time series is input into the proposed classification model to classify the failure modes and establish the failure mode weighted function. Finally, the feature time series is fed into the proposed regression model for RUL prediction with weighted processing to obtain accurate RUL predictions. Our experimental results demonstrate that our method effectively captures the degradation information of integrated circuits and generates precise RUL predictions. We demonstrate the efficacy of our method on a circuit stimulation model, showing that it outperforms several state-of-the-art RUL prediction methods. Our proposed method has the potential to enhance the reliability and safety of electronic devices in various applications.
This paper considers distributed optimization for minimizing the average of local nonconvex cost functions, by using local information exchange over undirected communication networks. To reduce the required communicat...
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The increased demand for active control of engines has made the study of high-frequency response actuators increasingly important, and actuators based on magnetostrictive materials are promising for a wide range of ap...
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ISBN:
(数字)9798350304947
ISBN:
(纸本)9798350304954
The increased demand for active control of engines has made the study of high-frequency response actuators increasingly important, and actuators based on magnetostrictive materials are promising for a wide range of applications. In this paper, the magnetic field distribution and various thermal losses including Joule heat loss, eddy current loss and hysteresis loss inside the giant magnetostrictive actuator (GMA) are analyzed, and the mathematical model of the current-driven GMA operation is derived, where the new J-A model considering the temperature effect is used to describe the hysteresis nonlinearity of the material. This paper simulates the actuator model under the action of multiple physical fields in COMSOL, focusing on the variation of the output displacement of the actuator when the thermal field and thermal expansion are integrated, and provides the theoretical basis for the design of the GMA control algorithm in the future.
Since piezoelectric actuating mechanism generally operate in high frequency response state, fatigue life has become an important factor influencing the performance and reliability of the entire drive mechanism. In ord...
Since piezoelectric actuating mechanism generally operate in high frequency response state, fatigue life has become an important factor influencing the performance and reliability of the entire drive mechanism. In order to investigate whether the designed piezoelectric ceramic actuator meets the active control requirements of the aero-engine, the paper analyzes the fatigue characteristics and fatigue life of the piezoelectric ceramic materials and the micro displacement amplification mechanism with finite element analysis softwareˈ and the optimal spacing value is obtained by studying the effect of the flexible hinge spacing on the fatigue characteristics of the displacement amplifier. And then, the fatigue life of the displacement amplifier is analyzed based on the drive load spectrum of the aircraft during simulated flight, whose result is 340.93 hours. Finally, the fatigue life of the piezoelectric actuating mechanism is 32 minutes when loaded with full power, which meets the design target initially.
This paper considers the distributed bandit convex optimization problem with time-varying inequality constraints over a network of agents, where the goal is to minimize network regret and cumulative constraint violati...
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This paper presents a cardiac MRI image segmentation model based on an improved U-Net architecture. Accurate segmentation of cardiac MRI images is critical for the diagnosis and treatment of cardiovascular diseases, y...
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ISBN:
(数字)9798350355413
ISBN:
(纸本)9798350355420
This paper presents a cardiac MRI image segmentation model based on an improved U-Net architecture. Accurate segmentation of cardiac MRI images is critical for the diagnosis and treatment of cardiovascular diseases, yet existing U-Net models exhibit limitations in handling complex cardiac structures and multi-scale features. To address these challenges, this paper proposes two key enhancements. First, we propose a Multi-Dimensional Context Attention module, designed to improve the integration of global and local information within the skip connections, thereby enhancing segmentation accuracy for intricate cardiac structures. Furthermore, we propose a Reverse Feature Modulation module, which generates reverse masks and dynamically adjusts feature weights across different classes using adaptive weighting, effectively mitigating class imbalance issues in multi-class segmentation tasks and improving focus on difficult-to-segment regions. Experimental results demonstrate that the proposed model outperforms the standard U-Net on the ACDC dataset, achieving significant improvements in evaluation metrics such as the Dice coefficient. These enhancements underscore the model's efficacy and robustness in complex cardiac image segmentation tasks, offering new technical support for automated cardiovascular disease diagnosis.
The integration of visuotactile sensor technology with endoscopy enables the provision of tactile information for minimally invasive surgeries and other operations. This paper proposes a real-time sensing framework fo...
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ISBN:
(数字)9798350372601
ISBN:
(纸本)9798350372618
The integration of visuotactile sensor technology with endoscopy enables the provision of tactile information for minimally invasive surgeries and other operations. This paper proposes a real-time sensing framework for contact deformation pattern shape, providing a foundation for precise perception in miniaturized visuotactile sensors. Specifically, we first construct a Deformation Pattern shape Descriptor (DPSD) and then track the key points in the descriptor using optical flow to obtain contact deformation shape information. Through extensive qualitative and quantitative experiments, our proposed algorithm achieves an average perception accuracy of around 83.81% for contact pattern shapes. It demonstrates consistent perception accuracy across various contact force magnitudes, directions, and scenarios, highlighting its robustness. Additionally, compared to traditional marker-level methods, it achieves a notable 46.5% improvement in displacement field perception accuracy. This research elevates tactile perception to the dimension of contact pattern shape sensing and has the potential for application in miniaturized visual tactile sensors.
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