Wind field forecasting is crucial for human activities, but numerical weather prediction still has room to improve accuracy. In this paper, we formalize wind field forecast correction as a spatiotemporal sequence pred...
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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 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.
This paper aims to solve large-scale and complex isogeometric topology optimization problems that consumesignificant computational resources. A novel isogeometric topology optimization method with a hybrid parallelstr...
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This paper aims to solve large-scale and complex isogeometric topology optimization problems that consumesignificant computational resources. A novel isogeometric topology optimization method with a hybrid parallelstrategy of CPU/GPU is proposed, while the hybrid parallel strategies for stiffness matrix assembly, equationsolving, sensitivity analysis, and design variable update are discussed in detail. To ensure the high efficiency ofCPU/GPU computing, a workload balancing strategy is presented for optimally distributing the workload betweenCPU and GPU. To illustrate the advantages of the proposedmethod, three benchmark examples are tested to verifythe hybrid parallel strategy in this paper. The results show that the efficiency of the hybrid method is faster thanserial CPU and parallel GPU, while the speedups can be up to two orders of magnitude.
Previous deep learning-based super-resolution(SR)methods rely on the assumption that the degradation process is predefined(e.g.,bicubic downsampling).Thus,their performance would suffer from deterioration if the real ...
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Previous deep learning-based super-resolution(SR)methods rely on the assumption that the degradation process is predefined(e.g.,bicubic downsampling).Thus,their performance would suffer from deterioration if the real degradation is not consistent with the *** deal with real-world scenarios,existing blind SR methods are committed to estimating both the degradation and the super-resolved image with an extra loss or iterative ***,degradation estimation that requires more computation would result in limited SR performance due to the accumulated estimation *** this paper,we propose a contrastive regularization built upon contrastive learning to exploit both the information of blurry images and clear images as negative and positive samples,*** regularization ensures that the restored image is pulled closer to the clear image and pushed far away from the blurry image in the representation ***,instead of estimating the degradation,we extract global statistical prior information to capture the character of the *** the coupling between the degradation and the low-resolution image,we embed the global prior into the distortion-specific SR network to make our method adaptive to the changes of *** term our distortion-specific network with contrastive regularization as *** extensive experiments on synthetic and realworld scenes demonstrate that our lightweight CRDNet surpasses state-of-the-art blind super-resolution approaches.
Graph neural network (GNN) has gained increasing popularity in recent years owing to its capability and flexibility in modeling complex graph structure data. Among all graph learning methods, hypergraph learning is a ...
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Ethereum has received increasing attention as the first blockchain platform to support smart *** mining has become an important tool for analyzing Ethereum ***,existing methods have the disadvantage of covering partia...
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Ethereum has received increasing attention as the first blockchain platform to support smart *** mining has become an important tool for analyzing Ethereum ***,existing methods have the disadvantage of covering partial transactions and being vulnerable to privacy-enhancing *** this paper,we propose a scheme for transaction correlation with the node as an entity,which can cover all transactions while being resistant to privacy-enhancing *** timestamps relayed from N fixed nodes to describe the network properties of transactions,we cluster transactions that enter the network from the same source *** results show that our method can determine with 97%precision whether two transactions enter the network from the same source node.
The application of unmanned driving in the Internet of Things is one of the concrete manifestations of the application of artificial intelligence *** semantic segmentation can help the unmanned driving system by achie...
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The application of unmanned driving in the Internet of Things is one of the concrete manifestations of the application of artificial intelligence *** semantic segmentation can help the unmanned driving system by achieving road accessibility *** segmentation is also a challenging technology for image understanding and scene *** focused on the challenging task of real-time semantic segmentation in this *** this paper,we proposed a novel fast architecture for real-time semantic segmentation named *** from the existing work of Bilateral Segmentation Network(BiSeNet),DuFNet proposes a novel Semantic Information Flow(SIF)structure for context information and a novel Fringe Information Flow(FIF)structure for spatial *** also proposed two kinds of SIF with cascaded and paralleled structures,*** SIF encodes the input stage by stage in the ResNet18 backbone and provides context information for the feature *** from previous stages usually contain rich low-level details but high-level semantics for later *** convolutions embed in Parallel SIF aggregate the corresponding features among different stages and generate a powerful global context representation with less computational *** FIF consists of a pooling layer and an upsampling operator followed by projection convolution *** concise component provides more spatial details for the *** with BiSeNet,our work achieved faster speed and comparable performance with 72.34%mIoU accuracy and 78 FPS on Cityscapes Dataset based on the ResNet18 backbone.
As one of the essential steps to secure government data sharing,Identity Authentication(IA)plays a vital role in the processing of large ***,the centralized IA scheme based on a trusted third party presents problems o...
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As one of the essential steps to secure government data sharing,Identity Authentication(IA)plays a vital role in the processing of large ***,the centralized IA scheme based on a trusted third party presents problems of information leakage and single point of failure,and those related to key ***,herein,an effective IA model based on multiattribute centers is ***,a private key of each attribute of a data requester is generated by the attribute authorization *** obtaining the private key of attribute,the data requester generates a personal private ***,a dynamic key generation algorithm is proposed,which combines blockchain and smart contracts to periodically update the key of a data requester to prevent theft by external attackers,ensure the traceability of IA,and reduce the risk of privacy ***,the combination of blockchain and interplanetary file systems is used to store attribute field information of the data requester to further reduce the cost of blockchain information storage and improve the effectiveness of information *** results show that the proposed model ensures the privacy and security of identity information and outperforms similar authentication models in terms of computational and communication costs.
As wafer circuit width shrinks down to less than ten nanometers in recent years,stringent quality control in the wafer manufacturing process is increasingly *** to the coupling of neighboring cluster tools and coordin...
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As wafer circuit width shrinks down to less than ten nanometers in recent years,stringent quality control in the wafer manufacturing process is increasingly *** to the coupling of neighboring cluster tools and coordination of multiple robots in a multi-cluster tool,wafer production scheduling becomes rather *** a wafer is processed,due to high-temperature chemical reactions in a chamber,the robot should be controlled to take it out of the processing chamber at the right *** order to ensure the uniformity of integrated circuits on wafers,it is highly desirable to make the differences in wafer post-processing time among the individual tools in a multicluster tool as small as *** achieve this goal,for the first time,this work aims to find an optimal schedule for a dual-arm multi-cluster tool to regulate the wafer post-processing *** do so,we propose polynomial-time algorithms to find an optimal schedule,which can achieve the highest throughput,and minimize the total post-processing time of the processing *** propose a linear program model and another algorithm to balance the differences in the post-processing time between any pair of adjacent cluster *** industrial examples are given to illustrate the application and effectiveness of the proposed method.
Tomato(Solanum lycopersicum), an economically important vegetable crop cultivated worldwide, often suffers massive financial losses due to Phytophthora infestans(P. infestans) spread and breakouts. Arbuscular mycorrhi...
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Tomato(Solanum lycopersicum), an economically important vegetable crop cultivated worldwide, often suffers massive financial losses due to Phytophthora infestans(P. infestans) spread and breakouts. Arbuscular mycorrhiza(AM) fungi mediated biocontrol has demonstrated great potential in plant resistance. However, little information is available on the regulation of mycorrhizal tomato resistance against P. ***, microRNAs(miRNAs) sequencing technology was used to analyse miRNA and their targets in the mycorrhizal tomato after *** infection. Our study showed a lower severity of necrotic lesions in mycorrhizal tomato than in nonmycorrhizal controls. We investigated 35 miRNAs that showed the opposite expression tendency in mycorrhizal and nonmycorrhizal tomato after P. infestans infection when compared with uninfected P. infestans. Among them, miR319c was upregulated in mycorrhizal tomato leaves after pathogen infection. Overexpression of miR319c or silencing of its target gene(TCP1) increased tomato resistance to P. infestans, implying that miR319c acts as a positive regulator in tomato after pathogen infection. Additionally, we examined the induced expression patterns of miR319c and TCP1 in tomato plants exposed to salicylic acid(SA) treatment, and SA content and the expression levels of SA-related genes were also measured in overexpressing transgenic plants. The result revealed that miR319c can not only participates in tomato resistance to P. infestans by regulating SA content, but also indirectly regulates the expression levels of key genes in the SA pathway by regulating TCP1. In this study, we propose a novel mechanism in which the miR319c in mycorrhizal tomato increases resistance to P. infestans.
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