Data migration strategies (DMSs) improve the overall performance of hybrid memory systems by migrating frequently accessed (hot) data to faster memory. However, designing an efficient DMS is challenging since the key ...
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Kalman filter (KF) is increasingly attracted for sensorless control of surface permanent magnet synchronous motors (SPMSMs) due to its strong robustness against measurement and system noise. However, conventional meth...
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When humanoid robots attempt to walk on terrain such as shaking platforms,time-varying disturbances are introduced to the support *** abrupt changes of inclination angle can cause the robot to lose balance upon landin...
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When humanoid robots attempt to walk on terrain such as shaking platforms,time-varying disturbances are introduced to the support *** abrupt changes of inclination angle can cause the robot to lose balance upon landing,presenting significant challenges for balance control *** address this issue,we propose a novel divergent component of motion(DCM)-based time-varying disturbance walking(DCM-TVDW)*** method allows the robot to walk on rugged surfaces and helps to maintain dynamic balance when subjected to large time-varying *** the DCM-TVDW control method,we first adjust the robot's center of mass and stride height to adapt to transitions between different terrain types via a variable height stabilization method,and hold these quantities constant as base *** then combine DCM with the N-step capturability *** combination allows for dynamic balance through multi-step adjustments from the initially unstable region,thereby extending the robots stability *** and experimental results demonstrate that the DCM-TVDW method enables the SJ-Bruce robot to traverse a dynamically shaking platform with an inclination angle of approximately 22°.
Continuous search problems(CSPs), which involve finding solutions within a continuous domain, frequently arise in fields such as optimization, physics, and engineering. Unlike discrete search problems, CSPs require na...
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Continuous search problems(CSPs), which involve finding solutions within a continuous domain, frequently arise in fields such as optimization, physics, and engineering. Unlike discrete search problems, CSPs require navigating an uncountably infinite space, presenting unique computational challenges. In this work, we propose a fixed-point quantum search algorithm that leverages continuous variables to address these challenges, achieving a quadratic speedup. Inspired by the discrete search results, we manage to establish a lower bound on the query complexity of arbitrary quantum search for CSPs, demonstrating the optimality of our approach. In addition, we demonstrate how to design the internal structure of the quantum search oracle for specific problems. Furthermore, we develop a general framework to apply this algorithm to a range of problem types, including optimization and eigenvalue problems involving continuous variables.
The unique property of chirality is widely used in various *** the past few decades,a great deal of research has been conducted on the interactions between light and matter,resulting in significant technical advanceme...
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The unique property of chirality is widely used in various *** the past few decades,a great deal of research has been conducted on the interactions between light and matter,resulting in significant technical advancements in the precise manipulation of light field *** this review,which focuses on current chiral optics research,we introduce the fundamental theory of chirality and highlight the latest achievements in enhancing chiral signals through artificial nano-manufacturing technology,with a particular focus on mechanisms such as light scattering and Mie resonance used to amplify chiral *** providing an overview of enhanced chiral signals,this review aims to provide researchers with an indepth understanding of chiral phenomena and its versatile applications in various domains.
With the increasing demand for high-quality 3D holographic reconstruction, visual clarity and accuracy remain significant challenges in various imaging applications. Current methods struggle for higher image resolutio...
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Raman random fiber laser(RRFL) possesses rich physical properties of spectral, temporal, and spatial domains due to its unique feedback mechanism and complex nonlinear effects. Characterizing and controlling the micro...
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Raman random fiber laser(RRFL) possesses rich physical properties of spectral, temporal, and spatial domains due to its unique feedback mechanism and complex nonlinear effects. Characterizing and controlling the microscopic evolution dynamics of RRFL are crucial to driving breakthrough advances in fields such as inertial confinement fusion and fundamental physics. In this work, a novel experimental and theoretical analysis of the evolution of the temporal spectral correlations of the RRFL in the transition and steady states is conducted. In the transitional state, the microscopic dynamics of the RRFL excitation process is revealed comprehensively: the temporal-correlation growth curve contrasts with that of resonant-cavity lasers, and the formation and degradation of spectral correlation are observed. In the steady state, the overall spectrum is characterized by partial correlation, and the correlation characteristics of RRFL mainly originate from the spectral random spikes, which offers a novel dimension for the precise control of RRFL correlation. This work provides new insights into underlying physical properties of continuous broadband lasers, offering key guidance for laser design, control, and applications.
With the rise of encrypted traffic,traditional network analysis methods have become less effective,leading to a shift towards deep learning-based *** these,multimodal learning-based classification methods have gained ...
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With the rise of encrypted traffic,traditional network analysis methods have become less effective,leading to a shift towards deep learning-based *** these,multimodal learning-based classification methods have gained attention due to their ability to leverage diverse feature sets from encrypted traffic,improving classification ***,existing research predominantly relies on late fusion techniques,which hinder the full utilization of deep features within the *** address this limitation,we propose a novel multimodal encrypted traffic classification model that synchronizes modality fusion with multiscale feature ***,our approach performs real-time fusion of modalities at each stage of feature extraction,enhancing feature representation at each level and preserving inter-level correlations for more effective *** continuous fusion strategy improves the model’s ability to detect subtle variations in encrypted traffic,while boosting its robustness and adaptability to evolving network *** results on two real-world encrypted traffic datasets demonstrate that our method achieves a classification accuracy of 98.23% and 97.63%,outperforming existing multimodal learning-based methods.
Mangroves are crucial to the ecological security of the Earth and human *** management,conservation,and restoration are of great importance and necessitate the support of spatio-temporal information and multidisciplin...
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Mangroves are crucial to the ecological security of the Earth and human *** management,conservation,and restoration are of great importance and necessitate the support of spatio-temporal information and multidisciplinary knowledge such as biology and *** knowledge services such as plant atlas provide illustrated textual knowledge of ***,this kind of service is oriented to information retrieval and is incapable of effectively mining and utilizing fragmented knowledge from multi-source heterogeneous data,facing the problem of“massive data,rare knowledge”.Knowledge graphs are capable of extracting,organizing,and fusing the knowledge contained in massive data into semantic networks that can be understood and computed by *** provide a solution for the realization of intelligent knowledge *** on the urgent need for mangrove knowledge acquisition,formal representation,and intelligent services,this paper proposes a research prospect on mangrove knowledge graphs and knowledge *** first analyze the similarities and differences between various domain-specific concepts of *** this basis,we define the mangrove knowledge graph as a large-scale knowledge base that integrates multi-disciplinary knowledge and spatio-temporal information with mangrove ecosystems as the ***,we propose a research framework for mangrove knowledge services that can realize the transformation from multi-modal data to intelligent knowledge services,including multiple research levels such as ubiquitous data sensing and aggregation,knowledge organization and graph construction,and intelligent mangrove knowledge ***,the methods and workflow for constructing mangrove knowledge graphs are ***,we discuss the challenges and possible future directions of mangrove knowledge services in the smart era,including the construction of a mangrove knowledge system that integrates the domain-specific charac
The safety and energy-saving driven co-optimization of vehicle speed and energy management for fuel cell/battery hybrid electric vehicle (FCHEV) has become a research hotspot in automotive. However, in the existing re...
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