Anomaly detection stands as a critical element in securing space information networks (SINs). This paper delves into the realm of anomaly detection within dynamic networks, shedding light on established methodologies....
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Dilute magnetic materials may find applications in spin-dependent applications such as spintronics and spin thermoelectrics. The conventional approach to realizing such materials is by doping a host material with tran...
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Dilute magnetic materials may find applications in spin-dependent applications such as spintronics and spin thermoelectrics. The conventional approach to realizing such materials is by doping a host material with transition-metal and rare-earth elements, which has been widely pursued in developing dilute magnetic semiconductors. However, such an approach could face issues such as solubility and inhomogeneity. Here, we study the dilute magnetic compounds (DMCs), which contain magnetic elements in a relatively small percentage and have the magnetic atoms occupying well-defined (ordered) lattice sites. The diluteness is thus guaranteed by enthalpy, instead of entropy as in the doping approach. By screening the inorganic crystal structure database, we identify two DMCs, Mg6MnO8 and Bi12MnO20. Mg6MnO8 has a fcc Mn lattice and octahedral coordination. Bi12MnO20 has a bcc Mn lattice and tetrahedral coordination. By using first-principles calculations, we calculated magnetic exchange interaction, magnon spectra, and electronic band structures of these materials. The Mn-Mn distance in Mg6MnO8 and Bi12MnO20 is 5.926 and 8.839 Å, respectively. The exchange interaction in Mg6MnO8 is 4–5 meV, while for Bi12MnO20 the largest distance renders the exchange interaction less than 1 meV. Mg6MnO8 holds promise for realizing the antiferromagnetic spin Seebeck effect. Bi12MnO20 has a band gap of 3.5 eV (ignoring the Mn 3d states in the band gap) and may be further doped for spintronic applications.
Geographically replicating objects across multiple data centers improves the performance and reliability of cloud storage *** consistent replicas comes with high synchronization costs,as it faces more expensive WAN tr...
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Geographically replicating objects across multiple data centers improves the performance and reliability of cloud storage *** consistent replicas comes with high synchronization costs,as it faces more expensive WAN transport prices and increased *** replication is the widely used technique to reduce the synchronization *** replication strategies in existing cloud storage systems are too static to handle traffic changes,which indicates that they are inflexible in the face of unforeseen loads,resulting in additional synchronization *** propose quantitative analysis models to quantify consistency and synchronization cost for periodically replicated systems,and derive the optimal synchronization period to achieve the best tradeoff between consistency and synchronization *** on this,we propose a dynamic periodic synchronization method,Sync-Opt,which allows systems to set the optimal synchronization period according to the variable load in clouds to minimize the synchronization *** results demonstrate the effectiveness of our *** with the policies widely used in modern cloud storage systems,the Sync-Opt strategy significantly reduces the synchronization cost.
The intermittent and fluctuating solar irradiance makes photovoltaic (PV) power generation unstable, which brings great challenges to the power grid system. Existing deep learning-based PV power generation prediction ...
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In the foundry industries,process design has traditionally relied on manuals and complex theoretical *** the advent of 3D design in casting,computer-aided design(CAD)has been applied to integrate the features of casti...
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In the foundry industries,process design has traditionally relied on manuals and complex theoretical *** the advent of 3D design in casting,computer-aided design(CAD)has been applied to integrate the features of casting process,thereby expanding the scope of design *** technologies use parametric model design techniques for rapid component creation and use databases to access standard process parameters and design ***,3D models are currently still created through inputting or calling parameters,which requires numerous verifications through calculations to ensure the design *** process may be significantly slowed down due to repetitive modifications and extended design *** a result,there are increasingly urgent demands for a real-time verification mechanism to address this ***,this study proposed a novel closed-loop model and software development method that integrated contextual design with real-time verification,dynamically verifying relevant rules for designing 3D casting ***,the study analyzed three typical closed-loop scenarios of agile design in an independent developed intelligent casting process *** is believed that foundry industries can potentially benefit from favorably reduced design cycles to yield an enhanced competitive product market.
As deep learning grows rapidly, model training heavily relies on parallel methods and there exist numerous cluster configurations. However, current preferences for parallel training focus on data centers, overlooking ...
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Video surveillance is widely adopted across various sectors for purposes such as law enforcement, COVID-19 isolation monitoring, and analyzing crowds for potential threats like flash mobs or violence. The vast amount ...
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With the development of astronautics, satellite antenna as an important communication equipment has also gradually developed to large scale. In this paper, a novel ring truss deployable antenna mechanism is proposed. ...
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This research utilizes higher-order dependency relationships for the modeling of higher-order dependency networks from voluminous maritime flow data and introduces higher-order dependency mining to uncover critical po...
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Human-AI coordination aims to develop AI agents capable of effectively coordinating with human partners,making it a crucial aspect of cooperative multi-agent reinforcement learning(MARL).Achieving satisfying performan...
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Human-AI coordination aims to develop AI agents capable of effectively coordinating with human partners,making it a crucial aspect of cooperative multi-agent reinforcement learning(MARL).Achieving satisfying performance of AI agents poses a long-standing ***,ah-hoc teamwork and zero-shot coordination have shown promising advancements in open-world settings,requiring agents to coordinate efficiently with a range of unseen human ***,these methods usually assume an overly idealistic scenario by assuming homogeneity between the agent and the partner,which deviates from real-world *** facilitate the practical deployment and application of human-AI coordination in open and real-world environments,we propose the first benchmark for open and real-world human-AI coordination(ORC)called *** includes widely used human-AI coordination ***,within the context of real-world scenarios,ORCBench considers heterogeneity between AI agents and partners,encompassing variations in capabilities and observations,which aligns more closely with real-world ***,we introduce a framework known as Heterogeneous training with Communication(HeteC)for *** builds upon a heterogeneous training framework and enhances partner population diversity by using mixed partner training and frozen historical ***,HeteC incorporates a communication module that enables human partners to communicate with AI agents,mitigating the adverse effects of partially observable *** a series of experiments,we demonstrate the effectiveness of HeteC in improving coordination *** contribution serves as an initial but important step towards addressing the challenges of ORC.
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