Dear Editor,This letter focuses on the distributed optimal containment control of continuous-time multi-agent systems(CTMASs)with respect to the minimum-energy performance index over fixed *** achieve this,we firstly ...
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Dear Editor,This letter focuses on the distributed optimal containment control of continuous-time multi-agent systems(CTMASs)with respect to the minimum-energy performance index over fixed *** achieve this,we firstly investigate the optimal containment control problem using the inverse optimal control method,where all states of followers asymptotically converge to the convex hull spanned by the leaders while some quadratic performance indexes get minimized.A sufficient condition for existence of the distributed optimal containment control protocol is *** introducing the parametric algebraic Riccati equation(PARE),it is strictly proved that the global performance index can be used to approximate the standard minimumenergy performance index as the parameters tends to *** consequence,the standard minimum-energy cooperative containment control can be solved by local steady state feedback protocols.
Die-stacked dynamic random access memory(DRAM)caches are increasingly advocated to bridge the performance gap between the on-chip cache and the main *** fully realize their potential,it is essential to improve DRAM ca...
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Die-stacked dynamic random access memory(DRAM)caches are increasingly advocated to bridge the performance gap between the on-chip cache and the main *** fully realize their potential,it is essential to improve DRAM cache hit rate and lower its cache hit *** order to take advantage of the high hit-rate of set-association and the low hit latency of direct-mapping at the same time,we propose a partial direct-mapped die-stacked DRAM cache called *** design is motivated by a key observation,i.e.,applying a unified mapping policy to different types of blocks cannot achieve a high cache hit rate and low hit latency *** address this problem,P3DC classifies data blocks into leading blocks and following blocks,and places them at static positions and dynamic positions,respectively,in a unified set-associative *** also propose a replacement policy to balance the miss penalty and the temporal locality of different *** addition,P3DC provides a policy to mitigate cache thrashing due to block type *** results demonstrate that P3DC can reduce the cache hit latency by 20.5%while achieving a similar cache hit rate compared with typical set-associative caches.P3DC improves the instructions per cycle(IPC)by up to 66%(12%on average)compared with the state-of-the-art direct-mapped cache—BEAR,and by up to 19%(6%on average)compared with the tag-data decoupled set-associative cache—DEC-A8.
Synthetic aperture radar (SAR) ship detection plays a significant role in ocean monitoring. However, the current SAR ship detection methods face limitations in detecting small and dense ships. To address these issues,...
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In the past few decades, the study of collective motion phase transition process has made great progress. It is also important for the description of the spatial distribution of particles. In this work, we propose a n...
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In the past few decades, the study of collective motion phase transition process has made great progress. It is also important for the description of the spatial distribution of particles. In this work, we propose a new order parameter φ to quantify the degree of order in the spatial distribution of particles. The results show that the spatial distribution order parameter can effectively describe the transition from a disorderly moving phase to a phase with a coherent motion of the particle distribution and the same conclusion could be obtained for systems with different sizes. Furthermore, we develop a powerful molecular dynamic graph network(MDGNet) model to realize the long-term prediction of the self-propelled collective system solely from the initial particle positions and movement angles. Employing this model, we successfully predict the order parameters of the specified time step. And the model can also be applied to analyze other types of complex systems with local interactions.
The visual modeling method enables flexible interactions with rich graphical depictions of data and supports the exploration of the complexities of epidemiological ***,most epidemiology visualizations do not support t...
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The visual modeling method enables flexible interactions with rich graphical depictions of data and supports the exploration of the complexities of epidemiological ***,most epidemiology visualizations do not support the combined analysis of objective factors that might influence the transmission situation,resulting in a lack of quantitative and qualitative *** address this issue,we developed a portrait-based visual modeling method called+*** method considers the spatiotemporal features of virus transmission patterns and multidimensional features of objective risk factors in communities,enabling portrait-based exploration and comparison in epidemiological *** applied+msRNAer to aggregate COVID-19-related datasets in New South Wales,Australia,combining COVID-19 case number trends,geo-information,intervention events,and expert-supervised risk factors extracted from local government area-based *** perfected the+msRNAer workflow with collaborative views and evaluated its feasibility,effectiveness,and usefulness through one user study and three subject-driven case *** feedback from experts indicates that+msRNAer provides a general understanding for analyzing comprehension that not only compares relationships between cases in time-varying and risk factors through portraits but also supports navigation in fundamental geographical,timeline,and other factor *** adopting interactions,experts discovered functional and practical implications for potential patterns of long-standing community factors regarding the vulnerability faced by the *** confirmed that+msRNAer is expected to deliver visual modeling benefits with spatiotemporal and multidimensional features in other epidemiological analysis scenarios.
Modern software development has moved toward agile growth and rapid delivery,where developers must meet the changing needs of users *** such a situation,plug-and-play Third-Party Libraries(TPLs)introduce a considerabl...
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Modern software development has moved toward agile growth and rapid delivery,where developers must meet the changing needs of users *** such a situation,plug-and-play Third-Party Libraries(TPLs)introduce a considerable amount of convenience to ***,selecting the exact candidate that meets the project requirements from the countless TPLs is challenging for *** works have considered setting up a personalized recommender system to suggest TPLs for ***,these approaches rarely consider the complex relationships between applications and TPLs,and are unsatisfactory in accuracy,training speed,and convergence *** this paper,we propose a new end-to-end recommendation model called Neighbor Library-Aware Graph Neural Network(NLA-GNN).Unlike previous works,we only initialize one type of node embedding,and construct and update all types of node representations using Graph Neural Networks(GNN).We use a simplified graph convolution operation to alternate the information propagation process to increase the training efficiency and eliminate the heterogeneity of the app-library bipartite graph,thus efficiently modeling the complex high-order relationships between the app and the *** experiments on large-scale real-world datasets demonstrate that NLA-GNN achieves consistent and remarkable improvements over state-of-the-art baselines for TPL recommendation tasks.
Reachability query plays a vital role in many graph analysis *** researches proposed many methods to efficiently answer reachability queries between vertex *** many real graphs are labeled graph,it highly demands Labe...
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Reachability query plays a vital role in many graph analysis *** researches proposed many methods to efficiently answer reachability queries between vertex *** many real graphs are labeled graph,it highly demands Label-Constrained Reachability(LCR)query inwhich constraint includes a set of labels besides vertex *** researches proposed several methods for answering some LCR queries which require appearance of some labels specified in constraints in the *** that constraint may be a label set,query constraint may be ordered labels,namely OLCR(Ordered-Label-Constrained Reachability)queries which retrieve paths matching a sequence of ***,no solutions are available for ***,we propose DHL,a novel bloom filter based indexing technique for answering OLCR *** can be used to check reachability between vertex *** the answers are not no,then constrained DFS is ***,we employ DHL followed by performing constrained DFS to answer OLCR *** show that DHL has a bounded false positive rate,and it's powerful in saving indexing time and *** experiments on 10 real-life graphs and 12 synthetic graphs demonstrate that DHL achieves about 4.8-22.5 times smaller index space and 4.6-114 times less index construction time than two state-of-art techniques for LCR queries,while achieving comparable query response *** results also show that our algorithm can answer OLCR queries effectively.
Let N be a maximal discrete nest on an infinite-dimensional separable Hilbert space H,ξ=∑^(∞)_(n=1)en/2n be a separating vector for the commutant N',E_(ξ)be the projection from H onto the subspace[Cξ]spanned ...
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Let N be a maximal discrete nest on an infinite-dimensional separable Hilbert space H,ξ=∑^(∞)_(n=1)en/2n be a separating vector for the commutant N',E_(ξ)be the projection from H onto the subspace[Cξ]spanned by the vectorξ,and Q be the projection from K=H⊕H⊕H onto the closed subspace{(η,η,η)^(T):η∈H}.Suppose that L is the projection lattice generated by the projections(E_(ξ) 0 0 0 0 0 0 0 0),{(E 0 0 0 0 0 0 0 0):E∈N},(I 0 0 0 I 0 0 0 0) and *** show that L is a Kadison-Singer lattice with the trivial ***,we prove that every n-th bounded cohomology group H~n(AlgL,B(K))with coefficients in B(K)is trivial for n≥1.
On July 18, 2021, the PKU-DAIR Lab1)(data and Intelligence Research Lab at Peking University) openly released the source code of Hetu, a highly efficient and easy-to-use distributed deep learning(DL) framework. Hetu i...
On July 18, 2021, the PKU-DAIR Lab1)(data and Intelligence Research Lab at Peking University) openly released the source code of Hetu, a highly efficient and easy-to-use distributed deep learning(DL) framework. Hetu is the first distributed DL system developed by academic groups in Chinese universities, and takes into account both high availability in industry and innovation in academia. Through independent research and development, Hetu is completely decoupled from the existing DL systems and has unique characteristics. The public release of the Hetu system will help researchers and practitioners to carry out frontier MLSys(machine learning system) research and promote innovation and industrial upgrading.
The forecasting of sales data is a widely studied issue in the fields of artificial intelligence and time series forecasting. TCN (Temporal Convolutional Network) is the most adept at managing time series data among a...
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