作者:
He, YukeGao, TongLv, YongZhang, JingjingChina University of Geoscienceis
Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation Wuhan430074 China
Animal experiments should minimize pain and discomfort and maximize animal welfare to satisfy the experimental animal 3R principle. The quality of vital signs monitor results collected from conscious and stress-free r...
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Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present so...
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Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present some sufficient conditions for the exponential stability of a particular category of switched systems.
Background Three-dimensional(3D)shape representation using mesh data is essential in various applications,such as virtual reality and simulation *** methods for extracting features from mesh edges or faces struggle wi...
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Background Three-dimensional(3D)shape representation using mesh data is essential in various applications,such as virtual reality and simulation *** methods for extracting features from mesh edges or faces struggle with complex 3D models because edge-based approaches miss global contexts and face-based methods overlook variations in adjacent areas,which affects the overall *** address these issues,we propose the Feature Discrimination and Context Propagation Network(FDCPNet),which is a novel approach that synergistically integrates local and global features in mesh *** FDCPNet is composed of two modules:(1)the Feature Discrimination Module,which employs an attention mechanism to enhance the identification of key local features,and(2)the Context Propagation Module,which enriches key local features by integrating global contextual information,thereby facilitating a more detailed and comprehensive representation of crucial areas within the mesh *** Experiments on popular datasets validated the effectiveness of FDCPNet,showing an improvement in the classification accuracy over the baseline ***,even with reduced mesh face numbers and limited training data,FDCPNet achieved promising results,demonstrating its robustness in scenarios of variable complexity.
Continuous monitoring of dynamic blood pressure (BP) is crucial for cardiovascular status analysis and holds significant value in the clinical prevention and diagnosis of cardiovascular diseases. However, existing met...
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In recent decades, origami has transitioned from a traditional art form into a systematic field of scientific inquiry, characterized by attributes such as high foldability, lightweight frameworks, diverse deformation ...
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Learning-based methods have become mainstream for solving residential energy scheduling problems. In order to improve the learning efficiency of existing methods and increase the utilization of renewable energy, we pr...
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Learning-based methods have become mainstream for solving residential energy scheduling problems. In order to improve the learning efficiency of existing methods and increase the utilization of renewable energy, we propose the Dyna actiondependent heuristic dynamic programming(Dyna-ADHDP)method, which incorporates the ideas of learning and planning from the Dyna framework in action-dependent heuristic dynamic programming. This method defines a continuous action space for precise control of an energy storage system and allows online optimization of algorithm performance during the real-time operation of the residential energy model. Meanwhile, the target network is introduced during the training process to make the training smoother and more efficient. We conducted experimental comparisons with the benchmark method using simulated and real data to verify its applicability and performance. The results confirm the method's excellent performance and generalization capabilities, as well as its excellence in increasing renewable energy utilization and extending equipment life.
In this paper, we study the decentralized federated learning problem, which involves the collaborative training of a global model among multiple devices while ensuring data *** classical federated learning, the commun...
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In this paper, we study the decentralized federated learning problem, which involves the collaborative training of a global model among multiple devices while ensuring data *** classical federated learning, the communication channel between the devices poses a potential risk of compromising private information. To reduce the risk of adversary eavesdropping in the communication channel, we propose TRADE(transmit difference weight) concept. This concept replaces the decentralized federated learning algorithm's transmitted weight parameters with differential weight parameters, enhancing the privacy data against eavesdropping. Subsequently, by integrating the TRADE concept with the primal-dual stochastic gradient descent(SGD)algorithm, we propose a decentralized TRADE primal-dual SGD algorithm. We demonstrate that our proposed algorithm's convergence properties are the same as those of the primal-dual SGD algorithm while providing enhanced privacy protection. We validate the algorithm's performance on fault diagnosis task using the Case Western Reserve University dataset, and image classification tasks using the CIFAR-10 and CIFAR-100 datasets,revealing model accuracy comparable to centralized federated learning. Additionally, the experiments confirm the algorithm's privacy protection capability.
Inverse modeling is extensively applied in the design and tuning of microwave filters (MFs). Inverse models (IMs) take the features extracted from the high-dimensional electromagnetic parameters as input. How to make ...
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Multiscale structures require excellent multiphysical properties to withstand the loads in various complex engineering *** this study,a concurrent isogeometric topology optimization method is proposed to design multis...
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Multiscale structures require excellent multiphysical properties to withstand the loads in various complex engineering *** this study,a concurrent isogeometric topology optimization method is proposed to design multiscale structures with high thermal conductivity and low mechanical ***,the mathematical description model of multi-objective topology optimization for multiscale structures is constructed,and a single-objective concurrent isogeometric topology optimization formulation for mechanical and thermal compliance is ***,by combining the isogeometric analysis method,the material interpolation model and decoupled sensitivity analysis scheme of the objective function are established on macro and micro *** solid isotropic material with penalization method is employed to update iteratively the macro and microstructure topologies ***,the feasibility and advantages of the proposed approach are illustrated by several 2D and 3D numerical examples with different volume fractions,while the effects of volume fraction and different boundary conditions on the final configuration and multi-objective performance of the multiscale structure are *** show that the isogeometric concurrent design of multiscale structures through multi-objective optimization can produce better multi-objective performance compared with a single-scale one.
Carrier transport in colloidal quantum dot(CQD)films is strongly influenced by the interfacial coupling between ***,the shape of PbS CQDs synthesized using traditional methods results in random orientation relationshi...
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Carrier transport in colloidal quantum dot(CQD)films is strongly influenced by the interfacial coupling between ***,the shape of PbS CQDs synthesized using traditional methods results in random orientation relationships between the crystal facets in CQD films,limiting the coupling strength and the final performance of optoelectronic *** this study,post-synthesis surface treatment of PbS CQDs was employed to achieve facet control during secondary growth,manipulating the facets of PbS CQDs at the nanoscale to enhance interfacial coupling within CQD ***,mixed ligands of PbX_(2)(X=Br,I)and anhydrous sodium acetate were used to passivate the PbS CQDs,ensuring sufficient *** method combines facet passivation with strong coupling through the(100)facets of CQDs,thereby enhancing carrier mobility and improving device *** results showed that,compared to standard PbS CQD films,the electron and hole mobilities of the PbS CQD films subjected to secondary growth were significantly improved,with hole mobility increased by 6 *** fabricated using these films achieved a quantum efficiency of 33%at 1500 nm under 0 V bias,a threefold improvement compared to standard devices.
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